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Humanoid Trajectory Planning for Robot Based on Minimum-Jerk Model of Human Arm

Chengyun Wang, Jing Zhao

Year
2022
Citations
2

Abstract

In this paper, a humanoid motion planning method for robot trajectory is proposed in this paper. The pickup and delivery motion in human-robot interaction is firstly studied, and the relationship between the peak velocity and the motion distance in the reaching point motion of the human arm is extracted. Then, based on the minimum-jerk model, a new method to estimate reaching duration is established. The algorithm can more accurately estimate the human arm's motion duration. Finally, the motion law of the human arm is applied to the humanoid trajectory planning of robots. The results show that the humanoid trajectory planning method can effectively improve the quality of human-robot interaction.

Keywords

Humanoid robotJerkTrajectoryMotion (physics)Motion planningComputer scienceRobotArtificial intelligenceRobotic armControl theory (sociology)

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