Personal robot assisting transportation to support active human life — Reference generation based on model predictive control for robust quick turning

Various robots are being developed to support active human lifestyles throughout the world. In particular, robots that can support a comfortable lifestyle for elderly people are needed for the coming super-aging society in many countries. The authors have already proposed the Personal Robot (PR) shown in Fig. 1, which can follow a human being and carry their baggage; the PR user does not need to carry heavy bags, even after shopping. The PR, therefore, can encourage not only elderly people but also young people to walk outside. This means that the PR can support a life of wellness in the true sense. In conventional research, a control approach for the roll angle is proposed to ensure the stability margin for steady turning because in order to follow a human being, the PR must realize high traveling performance. In this paper, a method of reference generation for the roll angle and turning angular velocity is proposed to take into account the stability margin during the transient state using model predictive control. According to the proposed approach, the quickest turning motion can be realized by keeping the upper and lower boundary constraints for the zero moment point (ZMP). The effectiveness of the proposed approach is verified by experiment using the prototype PR.