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ABSTRACT: We present a novel Weighted Barrier Function (WBF) method of efficiently computing optimal grasping force distributions for multifingered hands. Second-order conic friction constraints are not linearized, as in many previous works. The force distributions are smooth and rapidly computable, and they enable flexibility in selecting between firm, stable grasps or looser, more efficient grasps. Furthermore, fingers can be disengaged and re-engaged in a smooth manner, which is a critical capability for a large number of manipulation tasks. We present efficient solution methods that do not incur the increased computational complexity associated with solving the Semi-Definite Programming formulations presented in previous works. We present results from static and dynamic simulations which demonstrate the flexibility and computational efficiency associated with WBF force distributions.
Robotics and Automation (ICRA), 2010 IEEE International Conference on; 06/2010
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ABSTRACT: In this paper, we present a novel linear-program formulation that yields "optimally safe" (OS) tension distributions in parallel cable-driven robots by the introduction of a slack variable. The slack variable also enables explicit computation of a near-optimal, feasible starting point. This, in turn, enables rapid computation of the OS tension distributions. The formulation also contains a parameter that can be used to steer cable tensions toward desired regions of operation. We present static results from two simulated robotic systems that demonstrate the ability of our formulation to avoid tension limits. Simulated execution of highly dynamic trajectories on both systems demonstrates rapid-computation abilities. Furthermore, we present experimental results from a real robotic system that further validate the importance of safe tension distributions.
IEEE Transactions on Robotics 01/2010; · 2.54 Impact Factor
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ABSTRACT: Many sensing applications require monitoring phenomena with complex spatio-temporal dynamics spread over large spatial domains. Efficient monitoring of such phenomena would require an impractically large number of static sensors; therefore, actuated sensing - mobile robots carrying sensors - is required. Path planning for these robots, i.e., deciding on a subset of locations to observe, is critical for high fidelity monitoring of expansive areas with complex dynamics. We propose MUST - a multiscale approach with stochastic modeling. MUST is a hierarchical approach that models the phenomena as a stochastic Gaussian process that is exploited to select a near-optimal subset of observation locations. We discuss in detail our proposed algorithm for the application of monitoring light intensity in a forest understory. We performed extensive empirical evaluations both in simulation using field data and on an actual cabled robotic system to validate the effectiveness of our proposed algorithm.
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on; 11/2009
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ABSTRACT: We present the Networked InfoMechanical System for Planar Translation, which is a novel two-degree-of-freedom (2-DOF) cable-driven robot with self-calibration and online drift-correction capabilities. This system is intended for actuated sensing applications in aquatic environments. The actuation redundancy resulting from in-plane translation driven by four cables results in an infinite set of tension distributions, thus requiring real-time computation of optimal tension distributions. To this end, we have implemented a highly efficient, iterative linear programming solver, which requires a very small number of iterations to converge to the optimal value. In addition, two novel self-calibration methods have been developed that leverage the robot's actuation redundancy. The first uses an incremental displacement, or jitter method, whereas the second uses variations in cable tensions to determine end-effector location. We also propose a novel least-squares drift-detection algorithm, which enables the robot to detect long-term drift. Combined with self-calibration capabilities, this drift-monitoring algorithm enables long-term autonomous operation. To verify the performance of our algorithms, we have performed extensive experiments in simulation and on a real system.
IEEE Transactions on Robotics 11/2009; · 2.54 Impact Factor
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ABSTRACT: Energy efficiency presents a critical design challenge in wireless, wearable sensor technology, mainly because of the associated diagnostic objectives required in each monitoring application. In order to maximize the operating lifetime during real-life monitoring and maintain sufficient classification accuracy, the wearable sensors require hardware support that allows dynamic power control on the sensors and wireless interfaces as well as monitoring algorithms to control these components intelligently. This paper introduces a context-aware sensing technique known as episodic sampling - a method of performing context classification only at specific time instances. Based on additive-increase/multiplicative-decrease (AIMD), episodic sampling demonstrates an energy reduction of 85 percent with a loss of only 5 percent in classification accuracy in our experiment.
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE; 10/2009
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ABSTRACT: In this paper, we present results from a field-test of NIMS-PL, a redundantly actuated cable-driven robot for aquatic applications. We describe installation procedures that enable rapid deployability and present results demonstrating precise calibration capabilities. Detection and correction of positional drift, which is critical for long-term autonomous deployments, is demonstrated, and the rate of system drift is quantified. An example actuated sensing experiment is performed that accurately maps the spatiotemporal variation of the intensity of light incident on a swimming pool. Finally, we propose an upcoming, environmentally significant deployment in which we will map variations in aquatic phenomena such as salinity and pH through the confluence region of two rivers.
Automation Science and Engineering, 2009. CASE 2009. IEEE International Conference on; 09/2009
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ABSTRACT: We present NIMS3D, a novel 3-D cabled robot for actuated sensing applications. We provide a brief overview of the main hardware components. Next, we describe installation procedures, including novel calibration methods, that enable rapid in-field deployability for nonexpert end users, and provide simulations and experimental results to highlight their effectiveness. Kinematic and dynamic analysis of the system are provided, followed by a description of control methods. We provide experimental results that illustrate tracking of linear and nonlinear paths by NIMS3D. Thereafter, we briefly present an example of an actuated sensing task performed by the system. Finally, we describe methods of improving energy efficiency by leveraging nonlinear trajectories and energy-optimal tension distributions. Experimental and simulated results show that energy efficiency can be improved significantly by using optimized parabolic trajectories. Furthermore, we provide simulation results that demonstrate improved efficiency enabled by optimal, least norm tension distributions.
IEEE Transactions on Robotics 05/2009; · 2.54 Impact Factor
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ABSTRACT: Cabled robotic systems have been used for a diverse set of applications such as environmental sensing, search and rescue, sports and entertainment and air vehicle simulators. In this paper, we introduce a new cabled robot- Networked Info Mechanical System for Planar actuation (NIMS-PL), with energy profiling capabilities. Accurate energy measurements supported by NIMS-PL enable path planning that optimizes the robotpsilas path subject to an upper bound on energy consumption. We performed extensive empirical validation of the optimized path planning approach in simulation using an environmental sensing application as an example. We also validated the simulation results using NIMS-PL, demonstrating significant improvements in the sensing task when accounting with accurate energy measurements as opposed to Euclidean distance, which is typically used for modeling energy spent in path traversal.
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on; 10/2008
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ABSTRACT: The usage of conventional assistive cane devices is critical in reducing the risk of falls, which are particularly detrimental to the elderly and disabled. Individuals that experience the greatest risks rely on cane devices for support of ambulation. Results of many studies, however, have shown that incorrect cane usage is prevalent among cane users. The original SmartCane assistive system has been developed to provide a method for acquiring detailed motion data from cane usage. The cane itself, however, lacks any type of programmability as well as real-time data processing algorithms to provide feedback to the cane user. This paper describes the development of a real-time sensor information processing algorithm that provides direct detection of cane usage characteristics. Specifically, it supports direct feedback to the cane user, permitting guidance for proper cane usage and reducing the risk of falls. This paper also aims to improve upon the existing system by incorporating MicroLEAP, an energy-aware embedded computing platform. The new system provides local data processing capability by classifying whether an individual is executing a stride with proper cane motion and applied forces.
Medical Devices and Biosensors, 2008. ISSS-MDBS 2008. 5th International Summer School and Symposium on; 07/2008
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ABSTRACT: In this paper we describe an algorithm to generate energy efficient trajectories for NIMS3D, a three-dimensional cabled robotic platform. Optimized parabolic paths are used to exploit the relatively low I2R loss associated with operation in lower regions of the workspace. Trajectory optimization is sufficiently fast to enable real time operation. Experimental results on a physical system for a three cable deployment show substantial reductions in energy consumption as compared to linear trajectories.
Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on; 06/2008
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ABSTRACT: As concern for water resource availability increases, so does the need for intelligent aquatic sensing applications. The requirements, and complexity of such applications has also increased due to demands for: 1) broad spatial coverage and high spatial resolution monitoring, 2) capability for resolving fine scale spatiotemporal dynamics and 3) the need for rapid system deployment with semi-autonomous operation. With these criteria in mind, we present the Aquatic Networked InfoMechanical System (NIMS-AQ). NIMS-AQ was developed based on experience gained from engineering research and collaboration with aquatic scientists and environmental engineers during several in-field measurement campaigns [1], [2], [3]. In this paper we demonstrate the effectiveness of NIMS- AQ through two experimental sensing campaigns encompassing both river and lake environments. Each campaign is centered around critical water resource monitoring objectives such as temperature, flow and contaminant levels. Experimental results for autonomous depth profiling using a submersible sonar system as well as adaptive sampling algorithms guided by phenomena models are presented herein. The found results conform with our objectives for rapid and systematic operation. Preliminary studies also indicate the systems viability for use with an autonomous iterative experiment design for environmental applications (A-IDEA) methodology that is currently under development. The IDEA methodology [1] provides effective characterization of spatiotemporal dynamics in aquatic environments. A-IDEA, as it is to be implemented on the NIMS-AQ platform, is also described.
Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on; 06/2008
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ABSTRACT: High fidelity data acquisition of dynamic spatiotemporal phenomena for aquatic environmental research suggests the use of actuated sensors. Furthermore, characterization of the floor in aquatic environments is beneficial for environmental science, as well as can be applied to robot localization. The NIMS AQ cable robot platform is designed to meet these requirements and satisfy the constraints of large scale, in-field deployments. In addition to a set of water quality sensors it also carries an ultra-miniature side-scan sonar. In this paper we show the development of methods for autonomous range detection, spatial and semantic mapping in underwater environments. These methods are demonstrated to be important for future developments including localization, navigation, and path planning, particularly for 3D mobility. Experiments have been performed in both controlled environments and a lake environment and results are discussed.
Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on; 06/2008
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ABSTRACT: The usage of conventional assistive cane devices is critical in reducing the risk of falls, which are particularly detrimental for the elderly and disabled. Many of the individuals that experience the greatest risk of falling rely on cane devices for support of ambulation. However, the results of many studies have shown that incorrect cane usage is prevalent among cane users. The original SmartCane assistive system has been developed to provide a method for acquiring detailed motion data from cane usage. The cane itself, however, lacks any type of programmability as well as real-time data processing algorithms to provide feedback to the cane user. In this demonstration, we have incorporated an embedded computing platform into SmartCane and developed a real-time sensor information processing algorithm that provides direct detection of cane usage characteristics. The new system provides local data processing capability by classifying whether an individual is executing a stride with proper cane motion and applied forces. It also provides direct feedback information to the individual, thereby guiding the subject towards proper cane usage and reducing the risk of falls.
Information Processing in Sensor Networks, 2008. IPSN '08. International Conference on; 05/2008
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ABSTRACT: Extended system lifetime is a critical requirement for wearable sensor platforms. However, these platforms must also accommodate local data processing, data storage, and broadband wireless communications. Since compact battery storage capacity is constrained, there exists a fundamental tradeoff between energy optimization and performance. Furthermore, biomedical transducers may also demand high peak power dissipation during active operations. Energy management, therefore, must be introduced through new hardware architecture and enabled through software in the overall system design. To effectively optimize energy dissipation for biomedical sensing applications, a new wearable sensor platform, MicroLEAP, has been developed. The MicroLEAP platform supports per-task real-time energy profiling to permit adaptive applications that select platform components to best match dynamically-varying measurement requirements. MicroLEAP design, implementation, and example of energy-aware operation are demonstrated.
Biomedical Circuits and Systems Conference, 2007. BIOCAS 2007. IEEE; 12/2007
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ABSTRACT: In this paper we present algorithms that enable precise trajectory control of NIMS3D, an underconstrained, three-dimensional cabled robot intended for use in actuated sensing. We begin by offering a brief system overview and then describe methods to determine the range of operation of the robot. Next, a discrete-time model of the system is presented. Thereafter, we present an online algorithm for modeling motor behavior. The majority of the paper is dedicated to describing three feedback control laws used to enable accurate trajectory tracking for both linear and non-linear motion profiles. We present experimental results that highlight the strengths and weaknesses of these mechanisms and conclude by offering a series of future plans for NIMS3D.
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on; 12/2007
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ABSTRACT: This paper presents an incremental diagnosis method (IDM) to detect a medical condition with the minimum wearable sensor usage by dynamically adjusting the sensor set based on the patient's state in his/her natural environment. The IDM, comprised of a naive Bayes classifier generated by supervised training with Gaussian clustering, is developed to classify patient motion in- context (due to a medical condition) and in real-time using a wearable sensor system. The IDM also incorporates a utility function, which is a simple form of expert knowledge and user preferences in sensor selection. Upon initial in-context detection, the utility function decides which sensor is to be activated next. High-resolution in-context detection with minimum sensor usage is possible because the necessary sensor can be activated or requested at the appropriate time. As a case study, the IDM is demonstrated in detecting different severity levels of a limp with minimum usage of high diagnostic resolution sensors.
IEEE Transactions on Information Technology in Biomedicine 10/2007; · 1.68 Impact Factor
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ABSTRACT: Recent advancement in microsensor technology permits miniaturization of conventional physiological sensors. Combined with low-power, energy-aware embedded systems and low power wireless interfaces, these sensors now enable patient monitoring in home and workplace environments in addition to the clinic. Low energy operation is critical for meeting typical long operating lifetime requirements. Some of these physiological sensors, such as electrocardiographs (ECG), introduce large energy demand because of the need for high sampling rate and resolution, and also introduce limitations due to reduced user wearability. In this paper, we show how context-aware sensing can provide the required monitoring capability while eliminating the need for energy-intensive continuous ECG signal acquisition. We have implemented a wearable system based on standard widely-used handheld computing hardware components. This system relies on a new software architecture and an embedded inference engine developed for these standard platforms. The performance of the system is evaluated using experimental data sets acquired for subjects wearing this system during an exercise sequence. This same approach can be used in context-aware monitoring of diverse physiological signals in a patient's daily life.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: We present the design and theoretical analysis of a novel algorithm termed least recently visited (LRV). LRV efficiently and simultaneously solves the problems of coverage, exploration, and sensor network deployment. The basic premise behind the algorithm is that a robot carries network nodes as a payload, and in the process of moving around, emplaces the nodes into the environment based on certain local criteria. In turn, the nodes emit navigation directions for the robot as it goes by. Nodes recommend directions least recently visited by the robot, hence, the name LRV. We formally establish the following two properties: 1) LRV is complete on graphs and 2) LRV is optimal on trees. We present experimental conjectures for LRV on regular square and cube lattice graphs and compare its performance empirically to other graph exploration algorithms. We study the effects of the order of the exploration and show on a square lattice that with an appropriately chosen order, LRV performs optimally. Finally, we discuss the implementation of LRV in simulation and in real hardware.
IEEE Transactions on Robotics 09/2007; · 2.54 Impact Factor
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ABSTRACT: Low-cost sensors and wireless systems can now create a constantly vigilant and pervasive monitoring capability at home, at work, and in conventional point-of-care environments. While progress in this area is underway in sensor technology, mobile computing platforms, and data transport, barriers to large scale application remain ahead, particularly in the area of patient disease diagnosis, which generally requires a diverse set of sensors and instruments that are applied at proper times in response to patient state/behavior. As these sensors may be numerous, and may not be worn comfortably and practicably at all times, a solution is required for the systematic selection of sensors at the point of use. We describe the Incremental Diagnosis Method (IDM) system, an embedded decision support system based on Bayesian statistics and decision analysis theory developed to select or deselect available sensors so that the diagnostic certainty of patient condition best improved while the set of sensors used on the patient body is minimized. IDM has been evaluated in a testbed, the Medical Embedded Device for Individualized Care (MEDIC) system, based on standard, ubiquitous wireless platforms. MEDIC supports local sensing and signal processing, autonomous decision support, and remote reconfiguration and control of wearable components. A detailed evaluation of IDM operation and performance for patient gait analysis is also given in this paper. Finally, we also discuss the many new opportunities provided by IDM and the related future research introduced by this capability.
High Confidence Medical Devices, Software, and Systems and Medical Device Plug-and-Play Interoperability, 2007. HCMDSS-MDPnP. Joint Workshop on; 07/2007
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ABSTRACT: In this paper, we present NIMS RD, a rapidly deployable cable based robotic system developed for environmental monitoring applications. NIMS technology has been under continuous development resulting in several architectures including the NIMS RD system. This is an advance over previous systems in that its operation performance is improved, total system volume and mass is reduced, reliability is increased, and its deployment requires a smaller field team than for previous systems. The NIMS RD design will be described to highlight its new features and innovations. Also, NIMS RD field deployments will be discussed and some of the collected results displayed. Finally, future development directions for the NIMS RD system will also be discussed.
Robotics and Automation, 2007 IEEE International Conference on; 05/2007
