D. Vanhooydonck

École Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland

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Publications (20)0 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Elderly and disabled people can experience considerable difficulties when driving a powered wheelchair, especially if they do not possess the fine steering capacities that are required to perform certain manoeuvres, like avoiding obstacles or docking at tables. In order to help these people, several “intelligent” wheelchairs have been developed in the past, meaning that a powered wheelchair was endowed with the abilities to provide navigational assistance to its user. In such a scenario, control over the wheelchair is shared between the user and the intelligent assistance. The problem of the existing intelligent wheelchairs is, however, that the rules for assistance are hard-coded and by consequence not adaptable to the personal handicap and needs of a specific user. Therefore, this paper proposes a new, more user-centered approach to shared wheelchair control. The presented framework executes two tasks: it continuously estimates the user’s intention and it determines whether the user needs assistance to achieve that intention. An implicit user model is introduced and incorporated in the framework, in order to make the execution of both tasks adaptable to a specific user. This paper presents the proposed framework, along with experimental results in simulation and on a real wheelchair.
    Robotics and Autonomous Systems. 01/2010; 58:963-977.
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    ABSTRACT: In this paper we present further results of our asynchronous and non-invasive BMI for the continuous control of an intelligent wheelchair. Three subjects participated in two experiments where they steered the wheelchair spontaneously, without any external cue. To do so the users learn to voluntary modulate EEG oscillatory rhythms by executing three mental tasks (i.e., mental imagery) that are associated to different steering commands. Importantly, we implement shared control techniques between the BMI and the intelligent wheelchair to assist the subject in the driving task. The results show that the three subjects could achieve a significant level of mental control, even if far from optimal, to drive an intelligent wheelchair.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 01/2009; 2009:3361-4.
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    ABSTRACT: Many elderly and physically impaired people experience difficulties when maneuvering a powered wheelchair. In order to ease maneuvering, powered wheelchairs have been equipped with sensors, additional computing power and intelligence by various research groups. This paper presents a Bayesian approach to maneuvering assistance for wheelchair driving, which can be adapted to a specific user. The proposed framework is able to model and estimate even complex user intents, i.e. wheelchair maneuvers that the driver has in mind. Furthermore, it explicitly takes the uncertainty on the user’s intent into account. Besides during intent estimation, user-specific properties and uncertainty on the user’s intent are incorporated when taking assistive actions, such that assistance is tailored to the user’s driving skills. This decision making is modeled as a greedy Partially Observable Markov Decision Process (POMDP). Benefits of this approach are shown using experimental results in simulation and on our wheelchair platform Sharioto.
    Auton. Robots. 01/2008; 24:193-211.
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    ABSTRACT: The last years have witnessed a significant increase in the percentage of old and disabled people. Members of this population group very often require extensive help for performing daily tasks like moving around or grasping objects. Unfortunately, assistive technology is not always available to people needing it. For instance, steering a wheelchair can represent an extremely fatiguing or simply impossible task to many elderly or disabled users. Most of the existing assistance platforms try to help users without considering their specific needs. However, driving performance may vary considerably across users due to different pathologies or just due to temporary effects like fatigue. Therefore, we propose in this paper a user adapted shared control approach aimed at helping users in driving a power wheelchair. Adaption to the user is achieved by estimating the user's true intent out of potentially noisy steering signals before assisting him/her. The user's driving performance is explicitly modeled in order to recognize the user's intention or plan together with the uncertainty on it. Safe navigation is achieved by merging the potentially noisy input of the user with fine motion trajectories computed online by a 3D planner. Encouraging results on assisting a user who cannot steer to the left are reported on K.U.Leuven's intelligent wheelchair Sharioto.
    Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on; 12/2007
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    ABSTRACT: Many elderly and disabled people today experience difficulties when manoeuvring an electric wheelchair. In order to help these people, several robotic assistance platforms have been devised in the past. In most cases, these platforms consist of separate assistance modes, and heuristic rules are used to automatically decide which assistance mode should be selected in each time step. As these decision rules are often hard-coded and do not take uncertainty regarding the user's intent into account, assistive actions may lead to confusion or even irritation if the user's actual plans do not correspond to the assistive system's behavior. In contrast to previous approaches, this paper presents a more user-centered approach for recognizing the intent of wheelchair drivers, which explicitly estimates the uncertainty on the user's intent. The paper shows the benefit of estimating this uncertainty using experimental results with our wheelchair platform Sharioto
    Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on; 11/2006
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    ABSTRACT: This paper describes a novel adaptive filter approach to reduce the handicap a patient may experience when navigating an electric wheelchair. The filter automatically adapts to the specific handicap the patient has by training a connectionist structure that converts the joystick signal of the patient to the signal a reference user would give in the same context. Experimental results show that for various handicaps the filter improves the driving performance significantly
    Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium on; 10/2006
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    ABSTRACT: This paper presents an extension of current Global Dynamic Window approaches to arbitrarily shaped holonomic and non-holonomic mobile robots. The algorithm proceeds in two stages. In order to account for an arbitrary robot cross section, the first stage takes the robot's orientation explicitly into account by constructing a navigation function in the (x, y, θ) configuration space. In a second stage, an admissible velocity is chosen from a window around the robot's current velocity, which contains all velocities that can be reached under the acceleration constraints. Fast computation over large areas is achieved by adopting multi-resolution (x, y) and (x, y, θ) planning. Several measures are taken to obtain safe and robust robot behaviour. Experimental results on our wheelchair test platform show the feasibility of the approach.
    09/2006;
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    ABSTRACT: This paper presents an extension of current global dynamic window approaches to holonomic and nonholonomic mobile robots with an arbitrary cross-section. The algorithm proceeds in two stages. In order to account for an arbitrary robot footprint, the first stage takes the robot's orientation explicitly into account by constructing a navigation function in the (x, y, θ) configuration space. In a second stage, an admissible velocity is chosen from a window around the robot's current velocity, which contains all velocities that can be reached under the acceleration constraints. Fast computation over large areas is achieved by adopting multi-resolution (x, y) and (x, y, θ) planning. Several measures are taken to obtain safe and robust robot behaviour. Experimental results on our wheelchair test platform show the feasibility of the approach.
    Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on; 09/2005
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    ABSTRACT: Upcoming fast vision techniques for finding image correspondences enable reliable real-time visual homing, i.e. the guidance of a mobile robot from a arbitrary start pose towards a goal pose defined by an image taken there. Two approaches emerge in the field that differ in the fact that the structure of the scene is estimated or not. In this paper, we compare these two approaches for the general case and especially for our application, being automatic wheelchair navigation.
    Computational Intelligence in Robotics and Automation, 2005. CIRA 2005. Proceedings. 2005 IEEE International Symposium on; 07/2005
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    ABSTRACT: This paper reports on a robotic assistant for ambient intelligent meeting rooms and also for human-centred environments in general. The usefulness of such an "embodied" assistant as a video conferencing tool for sites not possessing an intelligent meeting room and as a mobile extension of an "intelliroom" is discussed, along with possible scenarios. The most important benefit is probably the more natural interaction between the human and the intelligent environment through this "embodied" assistant. This paper also proposes a hybrid approach for moving around in human-centred environments.
    12/2003;
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    ABSTRACT: Many elderly and disabled people today experience difficulties when maneuvering an electric wheelchair. In order to help these people, several robotic assistance platforms have been devised in the past. These platforms' architectures usually consist of separate assistance modes that each realise a specific navigation behaviour, such as "avoid-obstacles", or "drive-through-door". In most cases, heuristic rules are used to decide automatically which assistance mode should be selected in each time step. These decision rules are often hard coded and therefore not very adaptable to different user's actual plans do not correspond to the assistive system's behaviour. Moreover, navigation algorithms are used that take the wheelchair's kinematic and dynamic constraints only approximately into account. Consequently, these robotic wheelchairs may and do fail in executing the very same maneuvers with which elderly and disabled people have problems. In contrast with previous approaches, this paper presents a user-centered architecture for shared wheelchair control. The framework continuously estimates the user's intention explicitly before trying to assist him or her. The actual navigation assistance is performed by a fine motion planner that takes the kinematic and dynamic constraints into account. The paper presents experimental results and an evaluation of the architecture.
    Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on; 11/2003
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    ABSTRACT: This paper describes the recent steps taken at PMA in the development of a pair of legs for a humanoid robot. More specifically, the paper discusses the design of a decentralised motion control architecture for the robot. Several strong arguments for hierarchical and decentralised control are given. However, robust real-time and flexible implementation of such a decentralised architecture is not straightforward and should be handled with care. Therefore, some design principles to allocate responsibilities to the system's different modules are provided. Preliminary tests have shown a satisfactory robust real-time behaviour of the implemented architecture and have proven its feasibility.
    02/2003;
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    E Demeester, M Nuttin, D Vanhooydonck, H Van Brussel
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    ABSTRACT: Many elderly and disabled people today experience difficulties when manoeuvring an electric wheelchair. In order to help these people, several heuristic naviga-tion algorithms have been devised in the past. How-ever, in order to make the chair fast and reactive, the wheelchair's dimensions, non-holonomic and dynamic constraints are often only approximately taken into ac-count. Consequently, these robotic wheelchairs may and do fail in executing the very same manoeuvres with which the elderly and disabled have problems. A possible approach to tackle this problem, is to use a fine motion planner that takes the kinematic and dynamic constraints explicitly into account. This paper discusses the requirements for such wheelchair fine motion planners. Also, an enhanced version of a previously developed planner for autonomous robots is presented, and it is evaluated for use on wheelchairs.
    01/2003;
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    ABSTRACT: This paper r eports on a robotic a ssistant for ambient i ntelligent meeting rooms and also for human-centred environments in g eneral. The use- fulness of such an "embodied" a ssistant as a video conferencing tool for sites not possessing an intelligent meeting room and as a mobile e xtension o f an "intelliroom" is discussed, along with po ssible scenarios. The most i mportant benefit is probably the more natural interaction between the human and the in- telligent environment t hrough this "embodied" assistant. This paper also p ro- poses a hybrid approach for moving around in hu man-centred environments.
    Ambient Intelligence, First European Symposium, EUSAI 2003, Veldhoven, The Netherlands, November 3.-4, 2003, Proceedings; 01/2003
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    ABSTRACT: There are many user interfaces already available to drive electric wheelchairs. These enable users to convey their intention explicitly to the wheelchair control system. However, we have observed users who find it nonetheless extremely difficult to do so. For some severely disabled users it is almost impossible to drive a conventional electric wheelchair in a safe way. This paper explores several ways of implicit communication to assist the user to perform daily manoeuvres. Some initial user trials have been performed at a hospital. The results are evaluated and conclusions are drawn on the selection of suitable human-robot interaction techniques.
    Robot and Human Interactive Communication, 2002. Proceedings. 11th IEEE International Workshop on; 02/2002
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    ABSTRACT: People who suffer from paresis, tremor, spasticity etc. may experience considerable difficulties when driving electric wheel chairs. A sensor-based wheel chair may assist these users in their daily driving manoeuvres. There are two extreme cases: on the one hand, the wheel chair can be fully in control and on the other, the user can be fully in control. It is however difficult to determine a suitable level of shared autonomy situated in between these two extreme cases. This paper presents a framework for shared autonomy and addresses the issue of assessing the user’s autonomy.
    Autonome Mobile Systeme 2001, 17. Fachgespräch, Stuttgart, 11./12. Oktober 2001; 01/2001
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    E Demeester, M Nuttin, D Vanhooydonck, H Van Brussel
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    ABSTRACT: Many elderly and disabled people today experience difficulties when manoeuvring an electric wheelchair. In order to help these people, several navigation as-sistance architectures have been devised in the past. These usually consist of different modes that each re-alise a specific assistance behaviour such as "avoid-obstacle", "drive-through-door", or "dock-at-table". However, the user groups that need intelligent as-sistance are usually not able to select these modes themselves, or it may be a very time consuming task, thereby causing fatigue. This raises the need for an assistive robotic controller to select the appropriate mode automatically. Ideally, that mode is selected that corresponds maximally to the user's intention, other-wise confusion or even frustration may be experienced. Unfortunately, this user's intention is often not esti-mated explicitly in the current navigation assistance architectures. Instead, heuristic rules are used to de-cide which assistance behaviour should be activated. Furthermore, these decision rules are often hard coded and therefore not very adaptive to different users. In contrast with previous approaches, this pa-per presents a user-centered approach to intelligent wheelchair control. A probabilistic framework contin-uously estimates the user intention explicitly. In order to do so, the framework adopts a model of the user's driving behaviour. This way the navigation system can be made more adaptive to the user. Other goals of this approach are on-line evaluation of the user's driving capabilities, and on-line learning and tuning of the system.
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    ABSTRACT: Electric wheelchairs can provide necessary help to elderly or disabled people. If the people are unable to give precise and fine steering commands, an intelligent electric wheelchair can assist the driving by implementing a collision avoidance behaviour. However, a straightforward implementation of such an algorithm is not desired as the intent of the users is not always to avoid the obstacle (if for instance they want to dock at a table or pick a book from a shelf). A possible improvement is then to provide the users with assistance adapted to their intent. The problem is then to estimate when the users actually need assistance. To solve this task, we apply here a neural network technique, Reservoir Com- puting, which is a new and simple yet powerful way to use Recurrent Neural Networks.
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    ABSTRACT: The objective of this study is to assess the feasibility of controlling an asynchronous and non-invasive brain-actuated wheelchair by human EEG. Three subjects were asked to mentally drive the wheelchair to 3 target locations using 3 mental commands. These mental commands were respectively associated with the three wheelchair steering behaviors: \emph{turn left}, \emph{turn right}, and \emph{move forward}. The subjects participated in 30 randomized trials (10 trials per target). The performance was assessed in terms of percentage of reached targets calculated in function of the distance between the final wheelchair position and the target at each trial. To assess the brain-actuated control achieved by the subjects, their performances were compared with the performance achieved by a random BCI. The subjects drove the wheelchair closer than 1 meter from the target in 20\%, 37\%, and 7\% of the trials, and closer than 2 meters in 37\%, 53\%, and 27\% of the trials, respectively. The random BCI drove it closer than 1 and 2 meters in 0\% and 13\% of the trials, respectively. The results show that the subjects could achieve a significant level of mental control, even if far from optimal, to drive an intelligent wheelchair, thus demonstrating the feasibility of continuously controlling complex robotics devices using an asynchronous and non-invasive BCI.
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    ABSTRACT: Elderly and disabled people can experience consid-erable difficulties when driving an electric wheelchair, especially if they do not possess the fine steering capac-ities that are required to perform 'common' manoeu-vres, like avoiding obstacles, docking at tables, driv-ing through doors, etc. This paper describes a possi-ble approach to equip the wheelchair with an intelli-gent controller that performs low-level assistance, so wheelchair control is shared between the user and this controller. For proper operation, the controller should have a good idea of what the user wants in a particu-lar situation, or in other words what his/her intention could be. This text focuses on an 'implicit' estimation of the user's intention.