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Robotics and Autonomous Systems. 01/2010; 58:963-977.
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Auton. Robots. 01/2008; 24:193-211.
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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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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, October 9-15, 2006, Beijing, China; 01/2006
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Ambient Intelligence, First European Symposium, EUSAI 2003, Veldhoven, The Netherlands, November 3.-4, 2003, Proceedings; 01/2003
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Autonome Mobile Systeme 2001, 17. Fachgespräch, Stuttgart, 11./12. Oktober 2001; 01/2001
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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.
