| Summary: | 碩士 === 國立交通大學 === 電控工程研究所 === 103 === The wheelchair users often struggle to drive safely and accompanied by caregivers. Wheelchair robots can employ the autonomous functions to avoid obstacles and reduce the workload of the caregivers. To achieve the goal, the accompanist needs to be steadily recognized and tracked by the robots. A Q-learning based fuzzy controller (QLFC) is proposed to follow the accompanist. By judging the distance and orientation between the wheelchair robot and the human, Q values are updated by the designed reinforcement signals. The wheelchair robots can steadily follow the accompanist by self-learning controller. Meanwhile, it is important to make the people on wheelchair robots feel comfortable. Based on ISO 2631-1, the ride qualities are obtained by averaging the acceleration data in the frequency bands, and the critical thresholds utilizing to assess the ride comfort are also determined inside. To make the level of bumpiness be as multiple as possible, four kinds of pavements are chosen in the experiments. The results show that the feelings of the passengers on the wheelchair robot are quite different from the ride comfort defined in ISO 2631-1, so a new standard is proposed to assess the ride comfort in this study. The accuracy of the proposed standard is 90.67% which is higher than that of ISO 2631-1, 42.48%. Furthermore, to our best knowledge, this thesis is thought to be the first one to present the comfort criterion and assessment for wheelchair robots.
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