A Wheelchair Steered through Voice Commands and Assisted by a Reactive Fuzzy-Logic Controller
Journal of Intelligent and Robotic Systems
Context-based filtering for assisted brain-actuated wheelchair driving
Computational Intelligence and Neuroscience - EEG/MEG Signal Processing
IEEE Transactions on Robotics - Special issue on rehabilitation robotics
A new efficiency-weighted strategy for continuous human/robot cooperation in navigation
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ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A brain computer interface methodology based on a visual P300 paradigm
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Robotics and Autonomous Systems
Smart wheelchair control through a deictic approach
Robotics and Autonomous Systems
Brain-coupled interaction for semi-autonomous navigation of an assistive robot
Robotics and Autonomous Systems
Studies in Semi-Admissible Heuristics
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Mobility assistive devices and self-transfer robotic systems for elderly, a review
Intelligent Service Robotics
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This paper presents an Assistive Navigation System (ANS) for a Robotic Wheelchair (RW) relying on a Brain-Computer Interface (BCI), as the Human-Machine Interface (HMI). A two-layer collaborative control approach is proposed to steer the RW, taking into account both user and machine commands. The first layer, a virtual-constraint layer, is responsible for enabling/disabling the user commands, based on context. More specifically, user commands are enabled for a set of situations requiring user decision, namely, bifurcations, multiple-directions caused by new obstacles in the environment, and deadlocks. The second layer is a user-intent matching responsible for determining the suitable steering command that better fits the user selection, taking into account the user competence to steer the wheelchair, and situation awareness of potential directions at a given location. A P300-based BCI allows the selection of commands to steer the RW. Experimental results using RobChair (Pires and Nunes (2002) [7], Lopes et al. (2007) [42]) are presented, showing the effectiveness of the proposed methodologies. The ANS was validated with ten able-bodied participants, and one participant with cerebral palsy, in two different scenarios: a structured known environment, and a structured unknown environment with moving objects. The overall result was that all participants were able to successfully operate the device, showing a high level of robustness of both, the BCI system, and the navigation system.