National Natural Science Foundation of China grants Nos. 61573147, 91520201, and Guangzhou Research Collaborative Innovation Projects (No. 2014Y2-00507), Guangdong Science and Technology Research Collaborative Innovation Projects under Grant Nos. 2014B090901056, 2015B020214003, Guangdong Science and Technology Plan Project (Application Technology Research Foundation) No. 2015B020233006, and National High-Tech Research and Development Program of China (863 Program) (Grant No. 2015AA042303), and Foundation of State Key Laboratory of Robotics (No. 2014-o07).
In this paper, a human-machine shared control strategy is proposed for the navigation control of a wheelchair, employing both brain-machine control mode and autonomous control mode. In the brain-machine control mode, contrary to the traditional four-direction control signals, a novel brainmachine interface using steady state visual evoked potentials (SSVEP) is presented, which utilizes two brain signals to produce a polar polynomial trajectory (PPT). The produced trajectory is continuous in curvature without violating dynamic constraints of the wheelchair. In the autonomous control mode, the synthesis of angle-based potential field (APF) and vision-based SLAM (simultaneous localization and mapping) technique is proposed to guide the robot navigating among the obstacles. Extensive experiments have been conducted to test the developed shared control wheelchair in several scenarios with a number of volunteers, and the results have verified the effectiveness of the proposed shared control scheme.