Adaptive Attitude Control of Redundant Time-Varying Complex Model of Human Body in the Nursing Activity
Haiwei Dong, Zhiwei Luo, and Akinori Nagano
Department of Computational Science, Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan
With the development of human society, there are more and more elderly people need to be taken care of. However, there is not enough labor force to take the nursing jobs. Nowadays robots play more and more important roles in our daily life, especially in nursing activities. In this paper, we illustrate a new attitude control approach to lift human regardless of the individual differences, such as height, weight, and so on. In detail, considering our daily experience that only very few joints are critical for accomplishing the lifting up task, we treats the human body as a redundant system. We use robust adaptive control to eliminate the effects from the “uninterested joints” and identify the human parameters in real time. In addition, the convergence analysis, including tracking time and track error, is also given. The approach is simulated by lifting a human skeleton with two robot arms, which verifies the efficiency and effectiveness of our strategy.
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