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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (1): 523915-523915.doi: 10.7527/S1000-6893.2020.23915

• Dissertation • Previous Articles     Next Articles

Load distribution for space robots after target capture

ZHOU Yiqun1,2, LUO Jianjun1,2, WANG Mingming1,2   

  1. 1. Research&Development Institute, Northwestern Polytechnical University, Shenzhen, Shenzhen 518057, China;
    2. National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2020-02-29 Revised:2020-03-23 Published:2020-05-21
  • Supported by:
    Science, Technology and Innovation Commission of Shenzhen Municipality (JCYJ20190806154412671); National Natural Science Foundation of China (61973256, 61690211);Innovation Fundation for Doctor Dissertation of Northwestern Polytechnical University (CX202001)

Abstract: This paper proposes a load distribution method of the desired target external force for the multi-arm space robot after capturing the target in the form of soft-finger contact, which considers both the friction constraint and capability constraint of the manipulators. The dynamic equations of the space robotic system and the target are first constructed as the basis of load distribution. The soft-finger contact model between the end-effector of manipulators and the target surface is then established based on the research of ground robots, while the motion constraint between the two is also obtained. To simplify the optimization calculation, the friction cone constraint is linearized, and the capability constraint of manipulators considering the joint torque limit is established to transform the nonlinear optimization problem of the grasping force planning into a linear one. Finally, the numerical simulation of a dual-arm space robot model shows the effectiveness of the proposed method of load distribution for various forms of target motion.

Key words: multi-arm space robots, soft-finger contact, load distribution, capability constraint of manipulators, linear optimization

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