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Experimental validation of minimum-jerk principle in physical human-robot interaction
Chen Wang1,2; Liang Peng1; Zeng-Guang Hou1,2,3; Lincong Luo1,2; Sheng Chen1,2; Weiqun Wang1
2018
会议名称IEEE International Conference on Neural Information Processing (ICONIP)
会议日期2018-12-13
会议地点Siem Reap, Cambodia
摘要

Human motor control is a complex process, and undergoes changes due to the environmental interactions in physical human-robot interaction (pHRI). This pilot study aims to explore whether human motion under robotic constraints still complies with the same principles as in unconstrained situations, and how humans adapt to non-biological patterns of robot movements. Two typical modes in applications of pHRI (e.g., robot-assisted rehabilitation) are tested in this study. In humandominant mode, by building spring-damper force fields using a planar rehabilitation robot, we demonstrated that participants’ actual motion in reaching movements complied well with the standard minimum-jerk trajectory. However, when the virtual impedance between human force and virtual display was different from the human-robot physical impedance, the actual motion was also in a straight line but had a skewed bell-shaped velocity profile. In robot-dominant mode, by instructing participants to move along with the robot following biological or non-biological velocity
patterns, we illustrated that humans were better adapted to biological velocity patterns. In conclusion, minimum-jerk trajectory is a human preferred pattern in motor control, no matter under robotic force or motion constraints. Meanwhile, both visual feedback and haptic feedback are critical in human-robot cooperation and have effects on actual human motor control. The results of our experiments provide the background for modeling of human motion, prediction of human motion and trajectory planning in robot-assisted rehabilitation.
 

收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/44877
专题复杂系统认知与决策实验室_先进机器人
通讯作者Zeng-Guang Hou
作者单位1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.CAS Center for Excellence in Brain Science and Intelligence Technology
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Chen Wang,Liang Peng,Zeng-Guang Hou,et al. Experimental validation of minimum-jerk principle in physical human-robot interaction[C],2018.
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