Abstract
Smart wheelchair plays an important role in rehabilitation training and daily movement of people with high mobility disorders. To ensure that the smart wheelchair can operate stably in an unfamiliar environment, it is necessary to solve the problems of locating, mapping and motion planning. Facing the complex indoor environment of rehabilitation training and the wheelchair model, we propose a new smart wheelchair system design. Based on Simultaneous Localization and Mapping (SLAM) technology, location and mapping can be obtained through the Rao-Blackwellized Particle Filters (RBPF) algorithm. We integrate the sensor data into the proposal distribution to solve the particle degradation problem of RBPF and use selective resampling to improve the algorithm efficiency. According to the wheelchair’s own location and the surrounding environment map, global path planning and local real-time path planning are used to complete the motion planning. Experiments show that the smart wheelchair system we proposed can operate robustly and quickly in a complex indoor environment.
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