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Evaluation of Preference- and Constraint-Sensitive Path Planning for Assisted Navigation in Indoor Building Environments
Abstract
Independent mobility in people with physical disabilities notably enhances their quality of life by allowing social inclusion and promoting self-esteem while reducing caregiver burden. Despite significant technological advances in the last few decades, people with physical disabilities who rely on wheeled mobility devices continue to face significant challenges when independently navigating inside complex indoor environments. Several technological solutions have been explored to address this issue in previous work. Specifically, vision-based techniques that utilize fiducial markers as visual cues for assisted navigation have received particular attention because of their cost-effectiveness, reconfigurability, and ease of installation. Although such previous work addressed indoor localization for assisted navigation, it did not adequately address the fundamental aspects of indoor path planning, particularly in the context of considering human preferences or physical constraints present in the built environment. This paper addresses these key research gaps by developing fundamental rules for creating an indoor attribute-loaded graph network and a marker network map, developing a generic algorithm for determining optimal paths (instead of shortest paths only) from attribute-loaded networks, and integrating the findings within an interactive user interface (UI). As a precursor to eventual studies with people with mobility impairments, a scenario analysis followed by a preliminary usability study in a real physical environment involving 10 participants without disabilities was conducted to evaluate the navigation interface. Results demonstrate the feasibility of the proposed navigation system and provide design insights for improving the usability and performance of the current user interface.
... For an interfacing system like the one proposed in this study, proofof-concept implementation is used as verification to confirm that all the modules of the proposed system can work well with each other to reach the goal (Ge and Kuester 2014; Kim et al. 2012Kim et al. , 2021aKurien et al. 2018). Some studies also conducted user tests as the preliminary usability study (Akanmu et al. 2020;Chen et al. 2016;Mantha et al. 2020;Quintero et al. 2015). In this chapter, we presented three scenarios from the drywall installation case study as a proof-of-concept implementation. ...
... Twenty subjects, eleven female and nine male, were recruited and completed the experiment. Several prior studies have invited college students to test a system at its prototype stage to assist with system verification and design (Akanmu et al. 2020;Chen et al. 2016;Mantha et al. 2020;Quintero et al. 2015). Since the VR interface of the proposed system is fundamentally different from the traditional drywall installation approaches, we invited graduate students, who have basic knowledge of visualization and are more familiar with gaming and computer technologies, as the users for our study at this stage. ...
Human cognition plays a critical role in construction work, particularly in the context of high-level task planning and in-field improvisation. On the other hand, robots are adept at performing numerical computation and repetitive physical tasks with precise motion control. The unstructured and complex nature of construction environments and the inability to maintain tight tolerances in assembled workpieces pose several unique challenges to the wide application of robots in construction work. Thus, robotization of field construction processes is best achieved through human-robot partnerships that take advantage of both human and robot intelligence, as well as robots’ physical operational capabilities, to overcome uncertainties and successfully perform construction work. This dissertation explores the pathway of integrating building information models (BIM), interactive virtual reality (VR), and process-level digital twins to enable human-robot partnerships in digitally-driven construction through three levels. At the first level, an interactive and immersive process-level digital twin system in VR that serves as the human-robot collaboration platform is proposed. It integrates visualization and supervision, task planning and execution, and bi-directional communication to enable human workers to remotely collaborate with construction robots in field construction. A human-in-the-loop experiment based on a drywall installation case study was conducted for system verification and to collect user feedback for future improvements. Overall, the system enables human-robot partnerships and reduces the cognitive planning and physical workload of human workers. At the second level, Building Information Models (BIM) are integrated into the digital twin system to enable closed-loop BIM-driven Human-Robot Collaboration (HRC) in construction. BIM provides digital information to both the robot and its human partners to drive the construction process. In addition, deployment of the system to co-robotically performed construction work is studied. A physical drywall installation case study and three physical experiments (i.e., visual detection and end-effector movement) were conducted to verify the system workflow and to evaluate the system. Building on the previous level, the integration of BIM reduces human co-workers’ planning effort and improves construction work accuracy. Motivated by the programming and human instruction effort required to guide motion sequences in typical robotic work, the third level of this dissertation builds upon the BIM-driven digital twin system and explores how to enable robots to automatically plan their motion sequence. A Scene Distance Matrix (SDM) is proposed to guide robots’ sequential decisions in selecting modular construction skill primitives that lead to robot motions. Interactive Learning from Demonstration (LfD) is used to teach robots the mapping from the SDM to the skill primitives. The proposed approach is presented with a case study that contains three scenarios, including exterior wall sheathing, drywall installation, and timber frame construction. A wooden shelf construction task has been used to verify the proposed LfD module and its integration with the BIM-driven digital twin system. It further reduces the planning and programming effort of human workers. Overall, this research aims to create a scalable pathway to bring human workers in the loop of robotized construction and capitalize on human workers’ improvisation ability to handle uncertainties on construction sites. In addition, it explores the integration of BIM and LfD with the interactive digital twin to improve system autonomy in task planning and motion sequencing. This dissertation establishes the foundation of next-generation construction work by transitioning the role of construction workers from manual task performers to robot supervisors.
... For an interfacing system like the one proposed in this study, proof-of-concept implementation is used as verification to confirm that all the modules of the proposed system can work well with each other to reach the goal (Ge and Kuester 2015;Kim et al. 2012Kim et al. , 2021Kurien et al. 2018). Some studies also conducted user tests as the preliminary usability study (Akanmu et al. 2020;Chen et al. 2016;Mantha et al. 2020;Quintero et al. 2015). In this study, we presented three scenarios from the drywall installation case study as proof-of-concept implementation. ...
... There were 20 subjects, eleven female and nine male, who were recruited and completed the experiment. Several prior studies have invited college students to test a system at its prototype stage to assist with system verification and design (Akanmu et al. 2020;Chen et al. 2016;Mantha et al. 2020;Quintero et al. 2015). Since the VR interface of the proposed system is fundamentally different from the traditional drywall installation approaches, we invited graduate students, who have basic knowledge of visualization and are more familiar with gaming and computer technologies, as the users for our study at this stage. ...
Human cognition plays a critical role in construction work, particularly in the context of high-level task planning and in-field improvisation. On the other hand, robots are adept at performing numerical computation and repetitive physical tasks with precise motion control. The unstructured and complex nature of construction environments and the inability to maintain tight tolerances in assembled workpieces pose several unique challenges to the wide application of robots in construction work. Thus, the robotization of field construction processes is best conceived as a collaborative human-robot endeavor that takes advantage of both human and robot intelligence as well as robots' physical operation capabilities to overcome uncertainties and successfully perform useful construction work onsite. This paper proposes an interactive and immersive process-level digital twin (I2PL-DT) system in virtual reality (VR) that integrates visualization and supervision, task planning and execution, and bidirectional communication to enable collaborative human-robot construction work. In this work paradigm, the human worker is responsible for high-level task planning and work process supervision. The robot undertakes workspace sensing and monitoring, detailed motion planning, and physical execution of the work. A drywall installation case study involving imperfect rough carpentry (wall framing) is presented using a KUKA mobile industrial robotic arm emulator. A human-in-the-loop study involving 20 subjects was conducted for system verification and to collect feedback for future improvements. The experimental results show that users can use the system to specify work sequences, select optimal task plans, and perform robot trajectory guidance after simple training and felt positive about the system functions and user experience. The system demonstrates the potential of transitioning the role of construction workers from physical task performers to robot supervisors. In addition, the system establishes a promising framework for construction workers to remotely collaborate with onsite construction robots.
... Recently, (Mantha et al. 2020) utilized an indoor attribute-loaded graph network to take human preferences or physical constraints into account during path planning. Although a robotic assistive system in manual control can achieve high performance in global high-level planning, they are not effective with micro-level local planning and accuracy (Koontz et al. 2015). ...
As the number of Persons with Disabilities (PWD), particularly those with one or more physical impairments, increases, there is an increasing demand for assistive robotic technologies that can support independent mobility in the built environment and reduce the burden on caregivers. Current assistive mobility platforms (e.g., robotic wheelchairs) often fail to incorporate user preferences and control, leading to reduced trust and efficiency. Existing shared control algorithms do not allow the incorporation of the user control preferences inside the navigation framework or the path planning algorithm. In addition, existing dynamic local planner algorithms for robotic wheelchairs do not take into account the social spaces of people, potentially leading such platforms to infringe upon these areas and cause discomfort. To address these concerns, this work introduces a novel socially-aware shared autonomy-based navigation system for assistive mobile robotic platforms. Our navigation framework comprises a Global Planner and a Local Planner. To implement the Global Planner, the proposed approach introduces a novel User Preference Field (UPF) theory within its global planning framework, explicitly acknowledging user preferences to adeptly navigate away from congested areas. For the Local Planner, we propose a Socially-aware Shared Control-based Model Predictive Control with Dynamic Control Barrier Function (SS-MPC-DCBF) to adjust movements in real-time, integrating user preferences for safer, more autonomous navigation. Evaluation results show that our Global Planner aligns closely with user preferences compared to baselines, and our Local Planner demonstrates enhanced safety and efficiency in dynamic and static scenarios. This integrated approach fosters trust and autonomy, crucial for the acceptance of assistive mobility technologies in the built environment.
... It is observed that the disability type is often a decisive factor guiding the studies. The majority of the studies considering the disabled aim to facilitate the wheelchair users [1,2] or the visually impaired [3,4]. To the best of our knowledge, there is no work considering accessibility issues for the physically disabled, who can walk and climb stairs to some extent. ...
We observe that the majority of the studies regarding the walking impaired concentrate on wheelchair users. However, there are many people who are capable of walking in a limited way and not using wheelchairs. Our overall target working in this domain is a personally customizable navigation assistant for the physically disabled. Here, we present the theoretical steps toward this target. We propose a mathematical model for the area to be accessed using graphs. A survey study was carried out to determine some critical coefficients representing the relative difficulty of stair climbing and traveling on non-flat surfaces. The proposed algorithm takes in five personal parameters representing the individual’s physical capabilities and the graph representation of the area. First, it prunes the graph by eliminating the non-traversable edges for that person. If the source and destination nodes are still connected, an effort graph is obtained from the area graph considering the relative effort coefficients. Lastly, the minimum effort path is calculated on the effort graph. This three-stage algorithm and the graph structure we propose can lead to personally customizable navigation applications solving many accessibility problems faced by the disabled.
... Physically constrained people constitute a group of users which might benefit immensely from adjustments to conventional navigation systems. A proposed way of achieving this is by taking into account edge weights other than distances, thus considering specific user preferences such as avoiding stairs or minimizing turns which can be input directly by the user [30]. ...
Indoor navigation systems leverage shortest path algorithms to calculate routes. In order to define the “shortest path”, a cost function has to be specified based on theories and heuristics in the application domain. For the domain of indoor routing, we survey theories and criteria identified in the literature as essential for human path planning. We drive quantitative definitions and integrate them into a cost function that weights each of the criteria separately. We then apply an exhaustive grid search to find weights that lead to an ideal cost function. “Ideal” here is defined as guiding the algorithm to plan routes that are most similar to those chosen by humans. To explore which criteria should be taken into account in an improved pathfinding algorithm, eleven different factors whose favorable impact on route selection has been established in past research were considered. Each factor was included separately in the Dijkstra algorithm and the similarity of thus calculated routes to the actual routes chosen by students at the University of Regensburg was determined. This allows for a quantitative assessment of the factors’ impact and further constitutes a way to directly compare them. A reduction of the number of turns, streets, revolving doors, entryways, elevators as well as the combination of the aforementioned factors was found to have a positive effect and generate paths that were favored over the shortest path. Turns and the combination of criteria turned out to be most impactful.
... For a more different application, in [143], localization was achieved by a particle filter that combines BLE beacon fingerprinting and pedestrian dead reckoning, and the localization information was used to give blind people turn-byturn navigation instructions. It is natural to extend such an application to wheelchair users with physical disabilities to improve their independent mobility in unfamiliar environments [144]. In addition to the above applications, localization systems have also be extensively applied in construction for automatic data collection [15,145], construction management [146,147], construction site safety [148,149], and infrastructure inspection [6,150]. ...
Recent advances in robotics and enabling fields such as computer vision, deep learning, and low-latency data passing offer significant potential for developing efficient and low-cost solutions for improved construction and operation of the built environment. Examples of such potential solutions include the introduction of automation in environment monitoring, infrastructure inspections, asset management, and building performance analyses. In an effort to advance the fundamental computational building blocks for such applications, this dissertation explored three categories of scene understanding capabilities: 1) Localization and mapping for geometric scene understanding that enables a mobile agent (e.g., robot) to locate itself in an environment, map the geometry of the environment, and navigate through it; 2) Object recognition for semantic scene understanding that allows for automatic asset information extraction for asset tracking and resource management; 3) Distributed coupling analysis for system-level scene understanding that allows for discovery of interdependencies between different built-environment processes for system-level performance analyses and response-planning. First, this dissertation advanced Simultaneous Localization and Mapping (SLAM) techniques for convenient and low-cost locating capabilities compared with previous work. To provide a versatile Real-Time Location System (RTLS), an occupancy grid mapping enhanced visual SLAM (vSLAM) was developed to support path planning and continuous navigation that cannot be implemented directly on vSLAM’s original feature map. The system’s localization accuracy was experimentally evaluated with a set of visual landmarks. The achieved marker position measurement accuracy ranges from 0.039m to 0.186m, proving the method’s feasibility and applicability in providing real-time localization for a wide range of applications. In addition, a Self-Adaptive Feature Transform (SAFT) was proposed to improve such an RTLS’s robustness in challenging environments. As an example implementation, the SAFT descriptor was implemented with a learning-based descriptor and integrated into a vSLAM for experimentation. The evaluation results on two public datasets proved the feasibility and effectiveness of SAFT in improving the matching performance of learning-based descriptors for locating applications. Second, this dissertation explored vision-based 1D barcode marker extraction for automated object recognition and asset tracking that is more convenient and efficient than the traditional methods of using barcode or asset scanners. As an example application in inventory management, a 1D barcode extraction framework was designed to extract 1D barcodes from video scan of a built environment. The performance of the framework was evaluated with video scan data collected from an active logistics warehouse near Detroit Metropolitan Airport (DTW), demonstrating its applicability in automating inventory tracking and management applications. Finally, this dissertation explored distributed coupling analysis for understanding interdependencies between processes affecting the built environment and its occupants, allowing for accurate performance and response analyses compared with previous research. In this research, a Lightweight Communications and Marshalling (LCM)-based distributed coupling analysis framework and a message wrapper were designed. This proposed framework and message wrapper were tested with analysis models from wind engineering and structural engineering, where they demonstrated the abilities to link analysis models from different domains and reveal key interdependencies between the involved built-environment processes.
... Physically constrained people constitute a group of users which might benefit immensely from adjustments to conventional navigation systems. A proposed way of achieving this is by taking into account edge weights other than distances, thus considering specific user preferences such as avoiding stairs or minimizing turns which can be input directly by the user [30]. ...
Indoor navigation systems leverage shortest path algorithms to calculate routes. In order to define the "shortest path", a cost function has to be specified based on theories and heuristics in the application domain. For the domain of indoor routing, we survey theories and criteria identified in the literature as essential for human path planning. We drive quantitative definitions and integrate them into a cost function that weights each of the criteria separately. We then apply an exhaustive grid search to find weights that lead to an ideal cost function. "Ideal" here is defined as guiding the algorithm to plan routes that are most similar to those chosen by humans. To explore which criteria should be taken into account in an improved pathfinding algorithm, eleven different factors whose favorable impact on route selection has been established in past research were considered. Each factor was included separately in the Dijkstra algorithm and the similarity of thus calculated routes to the actual routes chosen by students at the University of Regensburg was determined. This allows for a quantitative assessment of the factors' impact and further constitutes a way to directly compare them. A reduction of the number of turns, streets, revolving doors, entryways, elevators as well as the combination of the aforementioned factors was found to have a positive effect and generate paths that were favored over the shortest path. Turns and the combination of criteria turned out to be most impactful.
... Mantha et al. also [18] proposed an architecture based on Mobile Augmented Reality to support the development of indoor navigation systems dedicated to wheelchair users. The architecture was capable of recognizing CAD drawings of the buildings and dealing with accessibility issues of wheelchair users. ...
One of the recurring issues mobility-impaired persons have to deal with is traveling alone in a wheelchair blindly without prior information regarding the accessibility of the planned route. Ordinary people usually choose the shortest path, but people with ambulant disabilities may prefer a longer route that does not include an uphill. The purpose of this paper is to extract the graph representation for people with reduced mobility across Baguio's Central Business District. The PWD ramps and wheelchair passable drop curbs were located with a smartphone GPS. Google Maps was used to verify the coordinates. The road distance was calculated using the Haversine formula as verified using Google Earth. The Lavene's Test for equality of variances and T-test of equality of means were used to check the significant difference between the derived values against Google's data. The derived latitude and longitude using a mobile phone's GPS did not differ significantly from the Google Maps coordinates. Moreover, the study showed that the calculated road distance using the Haversine formula did not vary considerably from the Google Earth distance. As such, the study aims to provide time and safety benefits by presenting a novel model representing the road network as a graph for mobility-impaired persons.
... Moreover, the safety, easiness and usability features in the assistive systems are considered a crucial requirement considering the special situation of mobility-impaired individuals. However, the currently available navigational assistive systems lack these features [32]. Highly impaired individuals, using the powered wheelchair, require an autonomous wheelchair for navigation [4]. ...
Several technological advancements emerged providing the technical assistance supporting people with special needs in tackling their everyday tasks. Particularly, with the advancements in cost-effective Brain-Computer Interfaces (BCI), they can be very useful for people with disabilities to improve their quality of life. This paper investigates the usability of low- cost BCI for navigation in an indoor environment, which is considered one of the daily challenges facing individuals with mobility impairment. A software framework is proposed to control a wheelchair using three modes of operations: brain- controlled, autonomous and semi-autonomous, taking into consideration the usability and safety requirements. A prototype system based on the proposed framework was developed. The system can detect an obstacle in the front, right and left sides of the wheelchair and can stop the movement automatically to avoid collation. The usability evaluation of the proposed system, in terms of effectiveness, efficiency and satisfaction, shows that it can be very helpful in the daily life of the mobility impaired people. An experiment was conducted to assess the usability of the proposed framework using the prototype system. Subjects steered the wheelchair using the three different operation modes effectively by controlling the direction of motion.
... The process of ambiguity resolution and fuzzification is precisely the opposite. It transforms the fuzzy output of the fuzzy inference system into a specific physical meaning [45][46][47][48][49]. The commonly used de-fuzzification methods include the gravity method, weighted summation method, area center method, and so on. ...
Building management systems are costly for small- to medium-sized buildings. A massive volume of data is collected on different building contexts by the Internet of Things (IoT), which is then further monitored. This intelligence is integrated into building management systems (BMSs) for energy consumption management in a cost-effective manner. Electric fire safety is paramount in buildings, especially in hospitals. Facility managers focus on fire protection strategies and identify where system upgrades are needed to maintain existing technologies. Furthermore, BMSs in hospitals should minimize patient disruption and be immune to nuisance alarms. This paper proposes an intelligent detection technology for electric fires based on multi-information fusion for green buildings. The system model was established by using fuzzy logic reasoning. The extracted multi-information fusion was used to detect the arc fault, which often causes electrical fires in the low-voltage distribution system of green buildings. The reliability of the established multi-information fusion model was verified by simulation. Using fuzzy logic reasoning and the membership function in fuzzy set theory to solve the uncertain relationship between faults and symptoms is a widely applied method. In order to realize the early prediction and precise diagnosis of faults, a fuzzy reasoning system was applied to analyze the arcs causing electrical fires in the lines. In order to accurately identify the fault arcs that easily cause electrical fires in low-voltage distribution systems for building management, this paper introduces in detail a fault identification method based on multi-information fusion, which can consolidate the complementary advantages of different types of judgment. The results demonstrate that the multi-information fusion method reduces the deficiency of a single criterion in fault arc detection and prevents electrical fires in green buildings more comprehensively and accurately. For the real-time dataset, the data results are presented, showing disagreements among the testing methods.
... This is usually achieved by first converting the existing built environment into a graphical network where the nodes represent the locations in the building, and the edges represent the physical links (e.g., corridors and stairs) connecting the nodes. Further details regarding converting building floor plans into a graphical network can be found in Mantha et al. (2018) and Mantha, Menassa, Kamat, and D'Souza (2019). The graphical network is then solved to determine an optimal path covering all the edges in the network so that the rogue sensor is not missed. ...
Digitalization and automation are making the architecture, engineering, and construction (AEC) industry more vulnerable to cyberattacks. Existing literature suggests that industry-specific studies need to be conducted. The work presented in this study shows a preliminary cybersecurity threat model relevant to the AEC industry. To that end, threat models for each of the life cycle phases are proposed. The feasibility of the proposed approach is illustrated with an example from the commissioning phase of a building, which includes an autonomous robotic system to collect data as a possible countermeasure. The suggested countermeasure shows promise to address some of the cybersecurity challenges faced in the building certification and commissioning process. The results show that the likelihood of detecting rogue sensors increases with additional constraints in the monitoring robot, such as minimum and maximum distance. The illustrative models suggest that the proposed framework will help to address the safety and cyber security of stakeholders and systems during crucial phases of construction projects.
... Kostic and Scheider [34] proposed a method for generating accessible space based on a grid model considering the shape of the agent and the wheelchair. Mantha et al. [35,36] simplified the navigation network by comparing the dimensions of the building structure and the dimensions of wheelchair agents. Liu and Zlatanova [37] presented an approach of calculating path for agents with different dimensions to avoid indoor obstacles in the 2D plane. ...
Most existing indoor navigation methods implicitly treat indoor users as ideal points. However, the ignorance of individual 3D indoor space needs may result in that navigation users do not have enough space or comfortable space to move in a real situation. Therefore, this paper proposes a novel human-oriented navigation approach that considers users' dimensions and interactions with indoor objects to establish comfortable navigable space. First, object space (O-Space) for users is derived according to their types (i.e., non-disabled people or disabled people) and functional space (F-Space) for indoor objects is determined according to their functions, locations, sizes, and interactions. Then, narrow gaps where users cannot pass through easily are calculated based on indoor obstacles defined by O-Space, the use of F-Space, and stationary objects. Finally, comfortable navigable space is established by excluding inappropriate sealed spaces that wrap indoor obstacles and narrow gaps of the entire indoor space. Two indoor navigation cases were conducted and the results demonstrate that our method could provide comfortable space and user-friendly paths that navigation users can navigate easily without stress. Furthermore, our method also shows great potential for improving user experience during navigation, especially in unfamiliar indoor environments and even emergencies.
... Accessibility attributes should include the following learning preferences, i.e., (1) physical preference, (2) cognitive preference, and (3) technological preference [25,26]. ...
Owing to the fast pace of growing educational needs, the deployment of smart educational tools along with highly productive and effective learning management systems are of supreme importance. Considering the advantages of classical flow theory, herein, we proposed a synergistic framework by combining the key elements of smart technology with a flow theory approach that can induce the overall learning efficacy with an added value of maintaining the smart learning and management environment. The given framework integrates numerous technological and communication tools to activate the learning process to adjust/maintain the requirements of different students under one umbrella. The proposed framework with positive outcomes can help to avoid discrimination and boost the confidence of low-level/low-grade students with a positive learning environment. Moreover, the learning efficacy and quality can be substantially improved via consistent monitoring and analyzing the student’s performance via information processing platforms based on the internet of things (IoT). However, designing the IoT applications for different level students in one class is a challenging issue and needs careful standardization. In this framework, this work aims to assist users in developing skills, adapt, and use technologies in a learning context to produce fruitful learning outcomes, which leads to big data.
... The aggregation of these edge distances is represented in the form of a matrix (i.e., cost matrix or C). To understand in-depth details on how and where nodes can be placed, edges can be formed, and other types of edge attributes can be found in Mantha et al. [57]. ...
Recent advancements in sensing and robotic technologies facilitate the use of on-demand building service robots in the built environment. Multi-robot based systems have arguably more advantages when compared to fixed sensor-based and single-robot based systems. These task-oriented building service robots face several challenges, such as task-allocation and route-planning. Previous studies adopted approaches from other domains, such as outdoor logistics, and made application-specific assumptions. This study proposes a new methodology to optimize the task-allocation and route-planning for multiple indoor robots with multiple starts and destination depots where each robot begins and ends at the same depot (referred to as a fixed destination multi-depot multiple traveling salesman problem-fMmTSP). The performance of the proposed algorithm was compared with two existing outdoor-based algorithms. Results show that the proposed algorithm performs better in almost all the cases for the assumed network, which supports the need to develop algorithms specifically for indoor networks .
... Accessibility attributes should include the following learning preferences, i.e., (1) physical preference, (2) cognitive preference, and (3) technological preference [25,26]. ...
Indoor navigation is difficult in large and complex navigation decision points. Helping occupants navigate more easily in these spaces is one of the important means to improve satisfaction. The navigation sign is an effective and one of the most common ways to achieve this goal. This study aims to propose a novel building information modeling based framework for designing navigation sign layout that better spatially matches the navigation cue demanded by occupants and the navigation cue supplied by signs. The demand for and supply of navigation cues are obtained from the crowd simulation and mathematical modeling, respectively. A programming model is applied to maximize the overlap between them by tuning the location of signs, the orientation of signs, and the navigation texts displayed on signs. To validate the effectiveness of the framework, the entrance lobby of a large hospital is used for the case study. An occupant navigation simulation model and a virtual reality based experiment are used for evaluating the sign layouts before and after implementing the proposed framework. The framework is supported to be effective in reducing the difficulty in navigation and navigation time.
Purpose
Shared autonomy has played a major role in assistive mobile robotics as it has the potential to effectively balance user satisfaction and smooth functioning of systems by adapting itself to each user’s needs and preferences. Many shared control paradigms have been developed over the years. However, despite these advancements, shared control paradigms have not been widely adopted as there are several integral aspects that have not fully matured. The purpose of this paper is to discuss and review various aspects of shared control and the technologies leading up to the current advancements in shared control for assistive mobile robots.
Methods
A comprehensive review of the literature was conducted following a dichotomy of studies from the pre-2000 and the post-2000 periods to focus on both the early developments and the current state of the art in this domain.
Results
A systematic review of 135 research papers and 7 review papers selected from the literature was conducted. To facilitate the organization of the reviewed work, a 6-level ladder categorization was developed based on the extent of autonomy shared between the human and the robot in the use of assistive mobile robots. This taxonomy highlights the chronological improvements in this domain.
Conclusion
It was found that most prior studies have focussed on basic functionalities, thus paving the way for research to now focus on the higher levels of the ladder taxonomy. It was concluded that further research in the domain must focus on ensuring safety in mobility and adaptability to varying environments.
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Implications for rehabilitation
• Shared autonomy in assistive mobile robots plays a vital role in effectively adapting to ensure safety while also considering the user comfort.
• User’s immediate desires should be considered in decision making to ensure that the users are in control of the assistive robots.
• The current focus of research should be towards successful adaptation of the assistive mobile robots to varying environments to assure safety of the user.
The digitalization and automation of the construction sector are transforming positively the way we plan, design, execute, and operate construction projects. However, they are also increasing the vulnerability of construction projects and making the architecture, engineering, construction, and facility management (AEC-FM) industry subject to cyberattacks. Although current cybersecurity practices are relevant, they cannot be directly adopted due to the unique challenges faced by the AEC-FM industry. Current literature suggests that industry-specific studies need to be conducted. To that extent, this study investigates the cybersecurity threat modeling for construction projects by developing a framework that identifies what might be compromised, how might it happen, why would someone intend to do it, what would be the impact, and what could be done to prevent it. The objectives are to a) develop a preliminary threat model relevant to construction, b) show the feasibility of the approach by using illustrative threat models for each of the life cycle phases, and c) use the commissioning phase of a building as a case study to show a possible countermeasure. The proposed framework will help to address the safety and security of stakeholders and systems during crucial phases of a construction project.
Due to their independence from environment instrumentation, Simultaneous Localization and Mapping (SLAM) based localization and navigation have received increasing attention and been widely applied for applications in the built environment and on construction sites. Compared with Lidar-based SLAM, the main concern with visual SLAM (vSLAM) is its effectiveness and robustness in challenging environments. As a major type of vSLAM algorithm, feature-based methods, including the state-of-the-art ORB-SLAM, rely on rich image features and a robust descriptor for matching feature correspondences across different image frames, which suffers from performance loss in environments with low-texture, low-structure areas (e.g., building corridors) or motion blur that are pretty common in practical applications. Regardless of being traditionally handcrafted or learned from recent data-driven methods such as convolutional neural networks (CNN), previous methods try to obtain an optimal fixed feature transform that works for any scenes.
With the aim of improving tracking robustness in challenging environments, as opposed to such fixed feature presentation, this research proposes and explores a learning-based dynamic feature transform that is self-adaptive towards recently observed scenes, which we termed as Deep SAFT. This paper also presents the design details of an implementation of Deep SAFT working with ORB-SLAM and evaluates the modified algorithm on fifteen popular public dataset sequences. The valuation results prove the feasibility and effectiveness of SAFT for improving the matching performance of learning-based descriptors. The proposed SAFT can be integrated with existing feature-based vSLAM algorithms to provide more robust locating service for applications either in the built environment (such as facility management) or on construction sites (such as construction site safety, construction progress monitoring, and infrastructure inspection).
Background
Accessibility implies making public places accessible to every individual, irrespective of his or her disability or special need, ensuring the integration of the wheelchair user into the society and thereby granting them the capability of participating in activities of daily living and ensuring equality in daily life.
Objective
This study was carried out to assess the accessibility of the physical infrastructures (public buildings) in the Kumasi metropolis to wheelchairs after the passage of the Ghanaian Disability Law (Act 716, 2006).
Methods
Eighty-four public buildings housing education facilities, health facilities, ministries, departments and agencies, sports and recreation, religious groups and banks were assessed. The routes, entrances, height of steps, grade of ramps, sinks, entrance to washrooms, toilets, urinals, automated teller machines and tellers’ counters were measured and computed.
Results
Out of a total of 84 buildings assessed, only 34 (40.5%) of the buildings, 52.3% of the entrances and 87.4% of the routes of the buildings were accessible to wheelchair users. A total of 25% (13 out of 52) of the public buildings with more than one floor were fitted with elevators to connect the different levels of floors.
Conclusion
The results of this study show that public buildings in the Kumasi metropolis are not wheelchair accessible. An important observation made during this study was that there is an intention to improve accessibility when buildings are being constructed or renovated, but there are no laid down guidelines as how to make the buildings accessible for wheelchair users.
The use of Big Data in today’s world has become a necessity due to the massive number of technologies developed recently that keeps on providing us with data such as sensors, surveillance system and even smart phones and smart wearable devices they all tend to produce a lot of information that need to be analyzed and studied in details to provide us with some insight to what these data represent. In this paper we focus on the application of the techniques of data reduction based on data nodes in large networks datasets by computing data similarity computation, maximum similarity clique (MSC) and then finding the shortest path in a quick manner due to the data reduction in the graph. As the number of vertices and edges tend to increase on large networks the aim of this article is to make the reduction of the network that will cause an impact on calculating the shortest path for a faster analysis in a shortest time.
Methods
Overall, five main functional requirements are proposed: the ability to allow for indoor navigation by means of Mobile Augmented Reality techniques; the capacity to register and configure building CAD drawings and the position of fiducial markers, points of interest and obstacles to be avoided by the wheelchair user; the capacity to find the best route for wheelchair indoor navigation, taking stairs and other obstacles into account; allow for the visualization of virtual directional arrows in the smartphone displays; and incorporate touch or voice commands to interact with the application. The architecture is proposed as a combination of four layers: User interface; Control; Service; and Infrastructure. A proof-of-concept application was developed and tests were performed with disable volunteers operating manual and electric wheelchairs.
Results
The application was implemented in Java for the Android operational system. A local database was used to store the test building CAD drawings and the position of fiducial markers and points of interest. The Android Augmented Reality library was used to implement Augmented Reality and the Blender open source library handled the basis for implementing directional navigation arrows. OpenGL ES provided support for various graphics and mathematical transformations for embedded systems, such as smartphones. Experiments were performed in an academic building with various labs, classrooms and male and female bathrooms. Two disable volunteers using wheelchairs showed no difficulties to interact with the application, either by entering touch or voice commands, and to navigate within the testing environment with the help of the navigational arrows implemented by the augmented reality modules.
Conclusion
The novel features implemented in the proposed architecture, with special emphasis on the use of Mobile Augmented Reality and the ability to identify the best routes free of potential hazards for wheelchair users, were capable of providing significant benefits for wheelchair indoor navigation when compared to current techniques described in the literature.
Mobility impaired people are often confronted with barriers along their chosen routes which lead to unreachable destinations and frustration. In order to assist this user group with finding barrier-free outdoor and indoor routes, we have developed a mobile application for Android devices which computes barrier-free routes between two locations on the basis of a personal profile. During our research, we tried to find other options to locate the user inside of a building, returning precise positions which can be calculated in real time without a high computing power and additional hardware. The starting position of a route is computed by using Bluetooth 4.0 transmitters which send UUIDs which was adapted by including the geo location of the transmitter into them. This allows us to compute the exact position of the user by trilateration of the signal strength of each transmitter. The ending point of the route is individually chosen by the user and is also returned as a geo location. Because we are using geo locations in decimal format, the results of our calculations can be displayed on every digital geographical map. The main difference to other solutions is, that we don’t use a special coordinate system for every building, instead we use the geolocations, which represent the coordinate system of the world and therefore, our developed technology can generally support a wide range of projects in the field of navigation. In addition, the result of our calculation can be displayed on every digital geographical map and is easily calculable to other widely used standards like WGS84, the common standard for current navigation devices. Instead of using special coordinate systems for every building, we use the geolocations, which represent the coordinate system of the entire world. That way, we are not only independent of additional coordinate information, but our navigation assistance works indoors as well as outdoors, as outdoor routing is based on the same geoid data. This makes our approach useable for a wide area of interests. This paper presents an innovative way to track users anywhere on our planet - even if they are inside of buildings - without using satellite communication for the determination of the position.
The operation and maintenance phase is the longest and most expensive life-cycle period of buildings and facilities. Operators need to carry out activities to maintain equipment to prevent functionality failures. Although some software tools have already been introduced, research studies have concluded that (1) facility handover data is still predominantly dispersed, unformatted and paper-based and (2) hence operators still spend 50% of their on-site work on target localization and navigation. To improve these procedures, the authors previously presented a natural marker-based Augmented Reality (AR) framework that digitally supports facility maintenance operators when navigating indoors. Although previous results showed the practical potential, this framework fails if no visual marker is available, if identical markers are at multiple locations, and if markers are light emitting signs. To overcome these shortcomings, this paper presents an improved method that combines an Inertial Measurement Unit (IMU) based step counter and visual live video feed for AR based indoor navigation support. In addition, the AR based marker detection procedure is improved by learning camera exposure times in case of light emitting markers. A case study and experimental results in a controlled environment reveal the improvements and advantages of the enhanced framework.
Whereas outdoor navigation systems typically rely upon global positioning system (GPS), indoor systems have to rely upon different techniques for localizing the user, as GPS signals cannot be received indoors. Over the past decade various indoor navigation systems have been developed. This paper provides a comprehensive overview of existing indoor navigation systems and analyzes the different techniques used for: (1) locating the user; (2) planning a path; (3) representing the environment and (4) interacting with the user. Our survey identifies a number of research issues that could facilitate large-scale deployment of indoor navigation systems.
This work proposes a Human-Comfortable Path Planner (HCoPP) system for autonomous passenger vehicles. The aim is to create a path planner that improves the feeling of comfort of the passenger, this topic is different from collision free planning and it has not received much attention. For this purpose, in addition to the shortest distance constraint conventionally used in path planning, constraints related to relevant environmental features are introduced. For straight segments, the constraint is based on the lane-circulation pattern preferred by humans. In curved segments and intersections, the constraint takes into account the visibility. A multi-layered cost map is proposed to integrate these additional constraints. To compute the human-comfortable path, a graph search algorithm was implemented. The evaluation of the proposed approach was conducted by having 30 participants riding an autonomous robotic wheelchair. The paths computed by the proposed path planner were compared towards a state of the art shortest-distance path planner implemented in the navigation stack of ROS. Experimental results show that the paths computed by the proposed approach are perceived as more comfortable.
In recent years, the interest and potential applications of pedestrian indoor navigation solutions have significantly increased.
Whereas the majority of mobile indoor navigation aid solutions visualize navigational information on mobile screens, the present
study investigates the effectiveness of a mobile projector-based navigation aid that directly projects navigational information
into the environment. A benchmark evaluation of the mobile projector-based indoor navigation interface was carried out, investigating
a combination of different navigation devices (mobile projector vs. mobile screen) and navigation information (map vs. arrow)
as well as the impact of users' spatial abilities. Results showed the superiority of the mobile screen as a navigation aid
and the map as a navigation information type. Especially users with low spatial abilities benefited from this combination
in their navigation performance and acceptance. Potential application scenarios and design implications for novel indoor navigation
interfaces are derived from our findings.
Location-based services, which can be applied in navigation systems, are a key application in mobile and ubiquitous computing. Combined with indoor localization techniques, pico projectors can be used for navigation purposes to augment the environment with navigation information. In the present empirical study (n = 24) we explore users' perceptions, workload and navigation performance when navigating with a mobile projector in comparison to a mobile screen as indoor navigation interface. To capture user perceptions and to predict acceptance by applying structural equation modeling, we assessed perceived disorientation, privacy concerns, trust, ease of use, usefulness and sources of visibility problems. Moreover, the impact of user factors (spatial abilities, technical self-efficacy, familiarity) on acceptance was analyzed. The structural models exhibited adequate predictive and psychometric properties. Based on real user experience, they clearly pointed out a) similarities and device-specific differences in navigation device acceptance, b) the role of specific user experiences (visibility, trust, and disorientation) during navigation device usage and c) illuminated the underlying relationships between determinants of user acceptance. Practical implications of the results and future research questions are provided.
This paper presents a new methodology for utilizing Augmented Reality (AR) fiducial markers on mobile devices (smart phone/tablet) for indoor Architecture, Engineering, Construction, and Facilities Management (AECFM) applications such as navigation and inspection. On one hand, previous efforts on such applications focused mainly on exploring traditional non-visual-sensor-based methods to track user's position continuously, ignoring the advantage that in most of the built environment, human inspectors can easily navigate themselves to destinations given that they can make correct decisions at a set of discrete critical spatial locations (corner of hallway, stairs etc.). On the other hand, traditionally fiducial markers are extensively used to recover user's pose and thus serve as table-top AR display surface, benefiting from its cost-efficiency and high flexibility. A different view that combines these two observations is to attach these markers at critical locations whose global positions and orientations are known in advance, treating markers as spatial indices which help the automatic identification of key locations. Upon recognizing the marker, as well as estimating the relative pose between the user and marker, user's pose in the global coordinate frame can be calculated. Then decisions can be automatically made and users are guided to their destinations by 3D graphical instructions. An example application for complex indoor environment way-finding is built on Android platform and tested which demonstrates the efficiency of the proposed method.
Background
Many people with mobility impairments, who require the use of powered wheelchairs, have difficulty completing basic maneuvering tasks during their activities of daily living (ADL). In order to provide assistance to this population, robotic and intelligent system technologies have been used to design an intelligent powered wheelchair (IPW). This paper provides a comprehensive overview of the design and validation of the IPW.
Methods
The main contributions of this work are three-fold. First, we present a software architecture for robot navigation and control in constrained spaces. Second, we describe a decision-theoretic approach for achieving robust speech-based control of the intelligent wheelchair. Third, we present an evaluation protocol motivated by a meaningful clinical outcome, in the form of the Robotic Wheelchair Skills Test (RWST). This allows us to perform a thorough characterization of the performance and safety of the system, involving 17 test subjects (8 non-PW users, 9 regular PW users), 32 complete RWST sessions, 25 total hours of testing, and 9 kilometers of total running distance.
Results
User tests with the RWST show that the navigation architecture reduced collisions by more than 60% compared to other recent intelligent wheelchair platforms. On the tasks of the RWST, we measured an average decrease of 4% in performance score and 3% in safety score (not statistically significant), compared to the scores obtained with conventional driving model. This analysis was performed with regular users that had over 6 years of wheelchair driving experience, compared to approximately one half-hour of training with the autonomous mode.
Conclusions
The platform tested in these experiments is among the most experimentally validated robotic wheelchairs in realistic contexts. The results establish that proficient powered wheelchair users can achieve the same level of performance with the intelligent command mode, as with the conventional command mode.
As technology becomes an increasingly vital aspect of modern social interaction, the field of disability informatics and web accessibility has made significant progress in consolidating theoretical approaches and exploring new application domains for those with motor and cognitive disabilities. Disability Informatics and Web Accessibility for Motor Limitations explores the principles, methods, and advanced technological solutions in the use of assistive technologies to enable users with motor limitations. This book is essential for academia, industry, and various professionals in fields such as web application designers, rehabilitation scientists, ergonomists, and teachers in inclusive and special education. This publication is integrated with its pair book Assistive Technologies and Computer Access for Motor Disabilities.
The objective of this study is to clarify the feasibility of recognition for performance of the Pointing and Calling. The Pointing and Calling is an activity that involves pointing at target objects by stretching our arm and stating out loud, “such and such is O.K.” at relevant points in the work in order to proceed with work safely and correctly. To facilitate the assessment for the enforcement of the Pointing and Calling by each worker, we developed a prototype system to recognize the performance of the activity. The recognition accuracy showed the feasibility of recognition by wearable sensors.
The paper presents global localization for a swarm of autonomous mobile robots which transport Euro-bins in a distribution center or warehouse. Localization is realized by sensor fusion of range measurements obtained from an IEEE 802.15.4a network and laser range finders. The IEEE 802.15.4a network is used for communication as well as for global localization. Laser range finders are used to detect landmarks and to provide accurate positioning for docking maneuvers. Range measurements are fused in a Monte Carlo Particle Filter. The paper presents the design of the network including the communication protocol together with the design of the localization algorithm. In order to support a large number of robots, the whole working area is divided into cells which use different frequencies. The network protocol provides handover between the cells and routing capabilities in real-time. Experimental results are given to prove the effectiveness of the proposed methods.
Integration of wheelchair bound individuals into the society requires accessibility to any building, especially public buildings in any part of the world. This study assessed the wheelchair accessibility of selected public buildings in Ibadan, Nigeria. Thirty-eight public buildings housing hospital, education, social and recreation centers and government ministry/agencies were surveyed. The doorway width, height of thresholds and steps, width of routes and grade of ramps were measured and computed. Accessibility was determined using an abridged form of the Americans with Disabilities Act Accessibility Guidelines (ADAAG). Only 7(18.4%) of the 38 buildings, 45.1% of the entrances and 19.4% of the routes were wheelchair accessible. The most accessible buildings were the hospitals (66.7%), while none of the social/ recreation buildings was accessible. This study revealed low level of wheelchair accessibility of public buildings in Ibadan, Nigeria, a factor that could limit opportunities for community integration of the wheelchair users.
Building engineers need access to real-time data to make retrofit decisions or improve the energy performance of the building occupants. Such data is typically gathered with the help of fixed wired and/or wireless sensors. Such a process consumes a significant amount of time, effort, and financial resources, particularly in existing buildings which do not have a Building Automation Systems (BAS) installed. This paper introduces a framework that uses autonomous mobile indoor robots for gathering actionable building information in real-time, and discusses how this information can be further utilized for various analyses and critical decision-making. The navigation and drift correction algorithms developed for autonomous robot operation are described in detail. Experimental results demonstrate the feasibility and applicability of the proposed method in large areas using only a sparse set of sensors mounted on mobile indoor robots. This research also developed a generic framework for making informed retrofit decisions with the help of robot collected data. A case study is performed to demonstrate the informed retrofit decision making process with the help of temperature data collected by a robot and subsequently used in an EnergyPlus simulation. Simulated annual energy savings of 3% were obtained by slightly modifying the R-values (20% to 45% improvement) of one of the external wall assemblies. These savings are expected to be larger if whole building retrofit and upgrade of material is performed. Thus, the proposed framework offers promise in improving the energy efficiency by extending the approach to other combinations of building materials (e.g. doors and windows).
Background: Integration of the wheelchair user into the society requires accessibility to any building, especially public buildings in any part of the world. Accessibility implies making public places accessible to every individual, irrespective of his or her disability or special need, ensuring the integration of the wheelchair user into the society and thereby rendering them the capability of participating in activities of daily living and ensuring equality in daily life.
Study Objective: This study was done to assess the accessibility of the physical infrastructures (public buildings) in the Kumasi metropolis to wheelchair users after the passage of the Disability Act.
Methods: Eighty four (84) public buildings housing the education, health, ministries, departments and agencies (MDA’s), sports/recreation, religious groups and banks were assessed. The routes, entrances, height of steps, grade of ramps, sinks, entrance to washrooms, toilets, urinals, automated teller machines, and tellers’ counters were measured and computed. Twenty one (21) managers of public buildings concerned also answered a structured questionnaire on accessibility concerns of their buildings. Accessibility was determined by using the abridged form of the Americans with Disability Act Accessibility Guidelines (ADAAG, 1990).
Results: Out of a total of 84 buildings assessed, only 34 (40.5%) of the buildings, 52.3% of the entrances and 87.4% of the routes of the buildings were accessible to wheelchair users. The results further showed that 14 out of 19 new public buildings whiles 20 out of 65 old public buildings were accessible to wheelchair users. And 29 out of 71 government buildings whereas 5 out of 13 private buildings were wheelchair friendly. A total of 25% (13 out of 52) public buildings with more than one floor were fitted with elevators to connect the different levels of floors. A total of 18 out of 21 managers of public institutions were aware of the disability act whiles only 10 of the managers know the details of the act.
Conclusion: The results of this study show that the wheelchair user will face many physical barriers in accessing public buildings and as such the public buildings in the Kumasi metropolis are not wheelchair friendly.
Robots have become increasingly pervasive in day-to-day life, simplifying several monotonous and mundane tasks in indoor environments. With increasing applications being developed for domestic service robots, recent research emphasis has shifted to autonomous indoor robots. Route planning (determining optimal routes to visit multiple locations) and task allocation (optimally dividing the tasks assigned among a group of robots) are two of the critical aspects that have to be accomplished by single and multiple autonomous robotic systems. Previous studies have attempted to adapt existing algorithms used in outdoor logistics applications and modify them with context-specific assumptions, often leading to inefficient or suboptimal solutions. This paper addresses these issues and proposes a generalized framework to solve the route-planning and task-allocation problems for centrally located service robots charged with spatiotemporal tasks in complex built environments. A scenario analysis is conducted to compare the performance of existing algorithms with the developed approach for route planning in building-monitoring robots. The results demonstrate the feasibility of the proposed approach in a range of applications involving constraints on both the environment (e.g., path obstructions) and robot capabilities (e.g., maximum travel distance on single charge).
Tended to view disability inclusion as merely another mandate, building and construction practitioners have yet to recognize its value in social sustainability. In academia, similarly, it has received less attention than other building performance attributes such as environmental friendliness and indoor air quality. With rights to access now acknowledged as basic human rights, there is demand for a tool to assess building disability inclusiveness, indicating the extent to which building considerations include persons with disabilities (PWDs). This paper proposes a Building Inclusiveness Assessment Score (BIAS) to fill the existing gap. The BIAS framework comprises two hierarchies of inclusion attributes identified from literature, guides, and standards of barrier-free access and universal design. The final product consists of two building disability inclusiveness assessment tools: the Physical Disability Inclusion Sub-score (PDIS) and the Visual Impairment Inclusion Sub-score (VIIS). These are simple, quantitative, objective tools for assessing buildings. We performed a Monte Carlo simulation
to validate the assessment protocols. Following the validation, we assessed 48 university buildings at four universities in Hong Kong to illustrate the real-life application of the tools.
Emergency response and pedestrian route planning rely highly on indoor–outdoor geospatial data and a network model of the data; however, indoor geospatial data collection is time-consuming. Several studies have used the architecture, engineering, and construction (AEC) model to generate indoor network models. These models are subject to the input data types, and the attributes of interior building objects are usually incomplete; hence, the integration of building information modeling (BIM) and geographic information systems (GIS) can benefit indoor–outdoor integrated applications. To achieve data interoperability, an open BIM standard called Industry Foundation Classes (IFC) is maintained by buildingSMART. In this study, we propose a multi-purpose geometric network model (MGNM) based on BIM and explore the strategy of indoor and outdoor network connections. To achieve the goals, the IFC-to-MGNM conversion includes the following: (1) extraction of building information from IFC, (2) isolation of the MGNM information from the aforementioned building information, and (3) build up the topological relationships of MGNM into GIS Geodatabase. In addition, an entrance-to-street strategy is proposed to connect indoor networks, entrances, and outdoor networks for detailed route planning. The experimental results indicate that the MGNM could be generated from BIM automatically and applied to connect indoor and outdoor features for the multi-purpose application. Two use-case scenarios were developed to validate the proposed methods. Compared to actual distance, the relative error was improved by 5.1% and 65.5% in the horizontal and vertical routes, respectively, over the conventional indoor network model from 2D ground plan. In addition, the computational time taken by the proposed coarse-to-fine route planning method was 25% that of the traditional single-scale route planning method.
The use of wheelchairs or other mobility aids often limits the community participation of people with disabilities because of architectural barriers present in buildings. Although this has been recognized as a global problem, little research has been done to document accessibility standards on an international level. This study reports results from a survey using the Americans With Disabilities Act Accessibility Guidelines Checklist for Buildings and Facilities to measure the differences in levels of accessibility in Albuquerque, New Mexico, United States, and Oaxaca, Oaxaca, Mexico. Investigators surveyed four building types (stores, restaurants, churches, and government buildings or public museums) in both geographic locations to determine whether each building was accessible. The findings showed that buildings in Albuquerque were significantly (p < .0001) more accessible than buildings in Oaxaca on all measurement items and across all four building types. However, many buildings in Albuquerque were not fully accessible.
In this paper, a robotic wheelchair using only a pan-tilt-zoom camera is proposed for developing a robotic system which enables a user to navigate in complex environment at low cost. For realizing the proposed system, a high accuracy visual marker, LentiBar which is capable of achieving a high level of precision in positioning and orienting a robotic wheelchair is utilized and its application to door crossing for a robotic wheelchair is presented. Since the visual marker is attached on the top of the target door through which the wheelchair is going to pass, the typical problems for achieving geometric features of the environment can be easily addressed. Door crossing navigation methods are also explained, which enable automatic and hybrid navigation of the robotic wheelchair. Finally, experimental results show the feasibility of the proposed navigation method and the robotic wheelchair system.
This article provides a comprehensive introduction into the simultaneous localization and mapping problem, better known in its abbreviated form as SLAM. SLAM addresses the problem of a robot navigating an unknown environment. While navigating the environment, the robot seeks to acquire a map thereof, and at the same time it wishes to localize itself using its map. The use of SLAM problems can be motivated in two different ways. One might be interested in detailed environment models, or one might seek to maintain an accurate sense of a mobile robot's location. SLAM servers both of these purposes. We review three major paradigms of algorithms from which a huge number of recently published methods are derived. First comes the traditional approach, which relies in the extended Kalman filter (EKF) for representing the robot's best estimate. The second paradigm draws its intuition from the fact that the SLAM problem can be viewed as a sparse graph of constraints, and it applies nonlinear optimization for recovering the map and the robot's locations. Finally, we survey the particle filter paradigm, which applies non-parametric density estimation and efficient factorization methods to the SLAM problem. This article discusses extensions of these basic methods. It elucidates variants of the SLAM problem and poses a taxonomy for the field. Relevant research is referenced extensively, and open research problems are discussed.
The proliferation of pedestrian navigation tools has made it challenging for users to avoid being confused and overwhelmed by the choices. Studies comparing mobile pedestrian navigation aides have generally based conclusions on either survey results from separate trials of exclusive interface usage or on performance of the interfaces as judged by the speed with which users are able to complete wayfinding tasks. However, it is not clear if users would mirror their individual trials or find a more strategic mixed-mode approach to using the tools at their disposal when given an option to choose from a set of tools. It is also unclear if users actually care about performance when choosing a navigation tool. We conducted a study to compare actual usage of navigation tools against user perception of the tools and performance with the tools in a series of wayfinding tasks. Results indicate that independent surveys can align well with extreme cases while performance may not actually be a good indicator of usage preferences.
Purpose
– The authors believe that people with cognitive and motor impairments may benefit from using of telepresence robots to engage in social activities. To date, these systems have not been designed for use by people with disabilities as the robot operators. The paper aims to discuss these issues.
Design/methodology/approach
– The authors conducted two formative evaluations using a participatory action design process. First, the authors conducted a focus group ( n =5) to investigate how members of the target audience would want to direct a telepresence robot in a remote environment using speech. The authors then conducted a follow-on experiment in which participants ( n =12) used a telepresence robot or directed a human in a scavenger hunt task.
Findings
– The authors collected a corpus of 312 utterances (first hand as opposed to speculative) relating to spatial navigation. Overall, the analysis of the corpus supported several speculations put forth during the focus group. Further, it showed few statistically significant differences between speech used in the human and robot agent conditions; thus, the authors believe that, for the task of directing a telepresence robot's movements in a remote environment, people will speak to the robot in a manner similar to speaking to another person.
Practical implications
– Based upon the two formative evaluations, the authors present four guidelines for designing speech-based interfaces for telepresence robots.
Originality/value
– Robot systems designed for general use do not typically consider people with disabilities. The work is a first step towards having our target population take the active role of the telepresence robot operator.
Disorientation has many costs. It may lead to physical fatigue, stress, and frustration and can also jeopardize people's safety. Designing wayfinding aids to fit people's needs can facilitate their environmental knowledge acquisition and, therefore, improve their wayfinding performance. The scope of this article is human wayfinding in unfamiliar buildings, considering only individual pedestrian movement in an immersive virtual environment. The purpose is to investigate the use of external information at a higher level of awareness (e.g., signage) as a wayfinding aid, as well as the use of immersive virtual reality (VR) to study indoor wayfinding. Fifty-four volunteers accomplished a wayfinding task (i.e., finding a room from the building's entrance) within a virtual building, employing two types of signage systems (i.e., vertical and horizontal conditions). A neutral condition (no signage) was also considered as a control condition to be used as a baseline. Aside from the success of the wayfinding task (getting to the destination), other performance metrics (distance traveled, time spent, number of pauses, and average speed) were analyzed and compared. Although the differences found are not statistically significant, findings suggest that participants assigned to the horizontal condition traveled smaller distances, spent less time, made fewer pauses, and moved at higher average speed than those assigned to vertical and neutral conditions. Gender-related differences were found statistically significant only in the average speed variable (females were faster than males). © 2012 Wiley Periodicals, Inc.
Accessibility information is necessary to support the everyday mobility of people with disabilities. As a service to aid the mobility of students with disabilities, some universities and colleges provide maps with accessibility information for their campus on the Web. Other maps, while not focused specifically on students, provide information about indoor accessibility and can be extended by users. In this paper, accessibility requirements published in the literature, the criteria used in existing geo-crowdsourcing services and the data used by campus accessibility maps (which are commonly based on the ADA standards) are used to provide an optimal set of requirements for personalized accessibility map (PAM). PAM is discussed and analysed in detail, a prototype PAM developed for the University of Pittsburgh is described, and challenges and future work are highlighted.
This work presents a proposal for an Ambient Assisted Wheelchair (A2W). Such a vehicle could collect useful information provided by Intelligent Environments equipped with appropriate wireless services. Two different networks have been considered for this tasks: a standard Wi-Fi network that will allow a connection to Internet Services providing building accessibility information; and a specific sensor network able to provide indoor location. The Buildings Accessibility Information Service (BAIS) is aimed for providing route planning in unknown indoor environments. BAIS system is based on a set of XML description files that contain all the information needed to access public or private buildings: floor maps, accessibility information, available routes and calibration landmarks. Sensor Network (SN) is based on a set of wireless nodes equipped with ZigBee devices; RSSI (Received Signal Strength Indication) from fixed nodes are used to compute an approximate 3D location that reinforces vehicle positioning inside buildings. Both resources BAIS and SN (when installed) could provide valuable information to any kind of user inside unknown environments, although best performances will be achieved with A2W units.
Physical disability becomes a major obstacle in the lives of physically challenged people and they are deprived of performing even their day-to-day activities without anybody's aid. One of the common problems they face is navigating their own home. So we proposed a system which aids such people to navigate their home or any indoor environment with all ease. Using this system not only can they reach any desired room in their home, they could also reach to the commonly used places inside a room such as sofa, television, refrigerator or any such commonly used places using voice commands. This can be done using the indoor positioning technique. The given area of the house is mapped into the system. The user's location is triangulated by applying lateration techniques such as time difference of arrival and angle of arrival. The location of the target places should be already marked which is essentially done using the same indoor positioning approach. A virtual line is drawn from the current location to the targeted location and the wheelchair is made to travel along the path calculating the coordinates dynamically and comparing with the already known coordinates of the line from the system thus making the wheelchair navigate correctly. We also provide an obstacle avoidance technique suitable for this type of navigation which detects dynamic obstacles present in the real time environment. This proposed system can be of immense use to various physically disabled people and thus making their lives easy without any external aid.
Based on wireless local area networks (WLAN), this paper presents the navigation of a robotic wheelchair. We propose a radio based robot localization with a particle filter by using received signal strength from WLAN. An intelligent strategy is proposed to select the informative WLAN signals and reduce the algorithm complexity. Furthermore, we introduce a graphic feature node extraction to explore the topology and linkages of a given graphic map. Based on the radio positioning and graphic map features, path planning can be provided for the task environment to accomplish the robot navigation with a fuzzy based behavior decision. Thus, the robotic wheelchair could response to the real dynamical environment. The experimental results conducted on real WLAN measurements indicate that the proposed approach provides the accurate localization and auto navigation services.
A robotic wheelchair system must be able to navigate outdoors as well as indoors. This paper describes the outdoor navigation system for our robotic wheelchair, Wheelesley, which uses a vision system to avoid obstacles and to stay centered on the current path. User tests were performed on 7 able-bodied subjects using single switch scanning on an outdoor course. The outdoor navigation system reduced user effort by 74% and reduced the time needed to navigate the test course by 20%. BACKGROUND The goal of this research is to provide people unable to drive a standard powered wheelchair with a mobility device that does not require the assistance of a caregiver. Robotic wheelchairs must be able to navigate in indoor and outdoor environments. A survey of powered and manual wheelchair users found that 56.6% used their wheelchair only outside, 33.3% used their wheelchair both inside and outside, and 10% used their wheelchair only inside (1). Most prior work on robotic wheelchairs has only addressed the problem of indoor navigation. This research project has developed a robotic wheelchair system that provides navigation assistance in indoor and outdoor environments, allowing its user to drive more easily and efficiently. Acoustic and vision based sensors are used to provide assistance. The wheelchair system is semi- autonomous, which takes advantage of the intelligence of the chair's user by allowing the user to plan the general route while taking over lower level control such as obstacle avoidance and centering on a path. The developed system has an easily customizable user interface that has been tested with eye tracking and with single switch scanning. This paper addresses the development and testing of the outdoor navigation system; for a full report on the wheelchair system, see (2). RESEARCH QUESTION Can assisted navigation in an outdoor environment improve driving performance when using single switch scanning as an access method? METHODS Sensors used in indoor environments, such as sonar and infrared, are not very effective in outdoor environments. Assistive navigation in an outdoor environment is accomplished using computer vision. We use a STH-V1 Stereo Head from Videre Designs mounted on the front of the wheelchair's tray to capture images of the world in front of the wheelchair. Disparities of points1 in the image are used to compute obstacle boundaries for obstacle avoidance. The navigation system also computes the location of the edges of the current path to provide path following. Obstacle avoidance takes priority over path following. The robot will only follow the command of the path following module if there are no obstacles detected. To detect obstacles, the disparity image is scanned horizontally and vertically, looking for changes in disparity between adjacent points that exceed a specified threshold, indicating a likely 1 Disparity measures the difference of the location of a point in the left and the right image of a stereo pair. Disparity is greater for closer objects and smaller for objects in the distance. You can experience this by looking ahead at a scene with some close and some far obstacles. Alternate closing your left and right eyes. Close objects will appear to move more from one image to the next than far objects do.
Single switch scanning is the access method of last resort for powered wheelchairs, primarily because drift is a significant problem. To correct a drift to the left or the right, the user must stop going forward, wait for the scanning device to get to the arrow for the direction of choice, click to turn the chair, stop turning, wait to scan to forward and then click to move forward again. Robotic assisted control can improve the ease and speed of driving using single switch scanning. Under robotic control, sensors are used to correct the drift problem and to avoid obstacles. The user is only required to give commands to change direction
Optimal cardiovascular, respiratory and motor activity assessment of wheelchair users using modern technologies of pervasive sensing and computing represents the main objective of the running project. In order to extract accurate information about physiological parameters provided by physical measurement channel and also to estimate additional parameters associated with virtual measurement channels advanced processing algorithms are implemented on embedded computing platform of the wheelchair. Will be implemented ballistocardiography, electrocardiography, plethysmography, skin conductance smart sensing devices that extract the health status information in unobtrusive way. The informations from the smart sensors, as from the localization units based on GPS technology (for outdoor localization) and RFID technology (for indoor localization) are processed on the embedded computing platform based on DSP that also assure the wireless data transmission to the human machine interface (HMI) expressed by a tablet that run mobile OS such as Android or Windows Mobile. A web based information system is used as part of the electronic health record that assure the remote health care assistance of the wheelchair users.
Keywords: Swarm Intelligence ; Collective Robotics ; SWARM_BOTS ; Evolutionary Robotics Note: Proceedings of the ANTS 2004, 4th International Workshop Sponsor: swarm-bots, OFES 01-0012-1 Reference LIS-BOOK-2004-002 URL: http://iridia.ulb.ac.be/~ants/ants2004/ Record created on 2006-01-12, modified on 2016-08-08
Although the regulations of the Americans with Disabilities Act (ADA) of 1990 were phased in by 1992, monitoring and enforcement continue to be problematic. This study of three large shopping centers in the Southwest included one mall that was opened in the mid-1990s, and two malls that were constructed prior to the law (but have undergone recent renovations). Use of the ADA Accessibility Guidelines Checklist for Buildings and Facilities ( Architectural and Transportation Barriers Compliance Board [ATBCB], 1992) generated data which were analyzed descriptively to determine the frequency and percent compliance in: parking lots, entrances, ramps, elevators, telephones, restrooms, food courts, and 12 specific store-types. No mall was fully compliant in any area, other than telephone specifications. In other areas, compliance ranged from 0% (ramp slopes in the newer mall) to many areas of 100% compliance (for example, outdoor curb ramps and food court seating spaces and aisles). The implications are that shoppers who are wheelchair mobile cannot count on complete compliance and cannot predict which physical architectural barriers they will find in shopping centers.
Access and mobility are important dimensions of quality of life. For wheelchair users, everyday trips are often fraught with problems, with many barriers imperceptible to the able-bodied, hindering or totally restricting movement. This paper describes a project undertaken with wheelchair users, which has developed, tested and applied a Geographic Information System model. This model acts both as a navigational device for wheelchairs users – enabling them to make informed route choices through urban places – and as a decision support and planning tool for urban planners – making visible the ways in which built environments are often distorted and hostile spaces for wheelchair users.
This paper presents an autonomous wheelchair system with the capability of self-localization and obstacle avoidance. In our
system, the ceiling lights are chosen as landmarks to realize the self-localization of the wheelchair, and a laser range-finder
is used for obstacle avoidance. First the approaches of landmark recognition and selflocalization for the wheelchair are proposed.
Then the principle of obstacle avoidance using a laser range-finder is described. Finally, the total system of the wheelchair
is introduced and a navigational experiment is described. Experimental results indicate the effectiveness of our system.
We consider a graph with n vertices, all pairs of which are connected by an edge; each edge is of given positive length. The following two basic problems are solved. Problem 1: construct the tree of minimal total length between the n vertices. (A tree is a graph with one and only one path between any two vertices.) Problem 2: find the path of minimal total length between two given vertices.
This paper addresses a novel method for localizing a stationary object in an indoor office environment. The proposed method utilizes the received-signal-strength index (RSSI) of radio signals radiating from fixed reference nodes and reference tags placed at known positions to generate a precise signal propagation model. Signal attenuation parameters are updated online according to environmental variation; thus, the proposed method has environmental-adaptation capabilities. Subsequent experiments were conducted to demonstrate the superiority of the proposed technique over a commercial location-based service (LBS) chipset.
Pedestrians with special needs encounter accessibility challenges and are exposed to even greater risks when using signalized traffic intersections. Even modern accessible pedestrian stations present significant challenges for pedestrians with physical and sight disabilities. This paper describes an interactive traffic controller for allowing the intersection to receive pedestrian call requests from users with special needs and for providing the user with guidance and signals status feedback information from the intersection. Feedback from the intersection enables individuals with low vision to know the state of the intersection, as well as receive guidance from the traffic controller based on the pedestrianpsilas location.