期刊
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
卷 28, 期 1, 页码 328-338出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2019.2958076
关键词
Shared control; Bayesian approach; brain machine interface; wheelchair robot
资金
- National Natural Science Foundation of China [61836003, 61573150, 61573152, 61633010]
- National Key Research and Development Project [2017YFB1002500]
- Fundamental Research Funds for the Central Universities [2019MS138, 2019MS113]
To enhance the performance of the brain-actuated robot system, a novel shared controller based on Bayesian approach is proposed for intelligently combining robot automatic control and brain-actuated control, which takes into account the uncertainty of robot perception, action and human control. Based on maximum a posteriori probability (MAP), this method establishes the probabilistic models of human and robot control commands to realize the optimal control of a brain-actuated shared control system. Application on an intelligent Bayesian shared control system based on steady-state visual evoked potential (SSVEP)-based brain machine interface (BMI) is presented for all-time continuous wheelchair navigation task. Moreover, to obtain more accurate brain control commands for shared controller and adapt the proposed system to the uncertainty of electroencephalogram (EEG), a hierarchical brain control mechanism with feedback rule is designed. Experiments have been conducted to verify the proposed system in several scenarios. Eleven subjects participated in our experiments and the results illustrate the effectiveness of the proposed method.
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