Chinese Space Science and Technology ›› 2025, Vol. 45 ›› Issue (3): 89-99.doi: 10.16708/j.cnki.1000.758X.2025.0041

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Design of continuum robot for space capture

YANG Chengxu1,ZHAO Zhijun1,*,WANG Yaobing1, WANG Jie1,WANG Lihua2   

  1. 1.Beijing Key Laboratory of Intelligent Space Robotic Systems, Beijing Institute of Spacecraft System Engineering
    Technology and Applications, Beijing 100094, China
    2.School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China
  • Received:2024-01-05 Revision received:2024-01-22 Accepted:2024-02-23 Online:2025-05-15 Published:2025-06-01

Abstract: Aiming at the requirement of reliable acquisition of objects of different sizes and shapes in space, a rope-driven continuum robot with “C” type linkage is designed, which can realize the “form-closed” and reliable capture of objects in the absence of some accurate measurement information. The continuum robot can be applied to the acquisition task of targets of different sizes by flexibly increasing or decreasing the number of joints, and has the characteristics of uniform operation capability in all directions. First the “C” type linkage design scheme of continuum robot is introduced, then the flexibility description index based on the Jacobian matrix condition number for the kinematic model of linkage continuum robot is established, and particle swarm optimization algorithm is adopted to optimize the rod length allocation of continuum robot with flexibility as the optimization objective. The results show that the flexibility index of the continuum robot with optimized rod length is 4.6% higher than that of the continuum robot with average rod length. Finally, the simulation results show that with the increase of the flexibility index, the anisodirectional motion ability of continuum robot becomes more similar. It is proved that the flexibility of continuum robot can be improved by using this index as optimization basis.

Key words: continuum robot, space capture, structure design, kinematic model, flexibility optimization