Sensors (Nov 2023)

A Pre-Grasping Motion Planning Method Based on Improved Artificial Potential Field for Continuum Robots

  • Lihua Wang,
  • Zezhou Sun,
  • Yaobing Wang,
  • Jie Wang,
  • Zhijun Zhao,
  • Chengxu Yang,
  • Chuliang Yan

DOI
https://doi.org/10.3390/s23229105
Journal volume & issue
Vol. 23, no. 22
p. 9105

Abstract

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Secure and reliable active debris removal methods are crucial for maintaining the stability of the space environment. Continuum robots, with their hyper-redundant degrees of freedom, offer the ability to capture targets of varying sizes and shapes through whole-arm grasping, making them well-suited for active debris removal missions. This paper proposes a pre-grasping motion planning method for continuum robots based on an improved artificial potential field to restrict the movement area of the grasping target and prevent its escape during the pre-grasping phase. The analysis of the grasping workspace ensures that the target is within the workspace when starting the pre-grasping motion planning by dividing the continuum robot into delivery and grasping segments. An improved artificial potential field is proposed to guide the continuum robot in surrounding the target and creating a grasping area. Specifically, the improved artificial potential field consists of a spatial rotating potential field, an attractive potential field incorporating position and posture potential fields, and a repulsive potential field. The simulation results demonstrate the effectiveness of the proposed method. A comparison of motion planning results between methods that disregard and consider the posture potential field shows that the inclusion of the posture potential field improves the performance of pre-grasping motion planning for spatial targets, achieving a success rate of up to 97.8%.

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