Applied Sciences (Jul 2023)

Model-Based Adaptive Collaboration of Multi-Terminal Internal Force Tracking

  • Zhala Wang,
  • Jingmin Dai,
  • Fei Song

DOI
https://doi.org/10.3390/app13158672
Journal volume & issue
Vol. 13, no. 15
p. 8672

Abstract

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This paper proposes a multi-terminal adaptive collaborative operation method for solving the problem of unstable internal force tracking in the clamping and handling of unknown objects by multi-terminal robots. In the proposed method, the internal command force changes the complex internal force control problem into an internal force tracking problem from multi-slave to master. Moreover, we develop an algorithm for multi-slave setups to estimate the object stiffness and motion uncertainty in the direction of the internal command force according to Lyapunov theory. Finally, the impedance control generates a reference trajectory for the multi-slave to maintain the desired internal force and track the master’s motion. Several experiments were conducted on a self-made robot. The experimental results show that the oscillation amplitude of each slave end is less than 1 mm and the directional oscillation amplitude is less than 1 degree during the tracking of the desired commanded internal force. For objects with a low stiffness, the error of the commanded internal force is less than 1 N (6%) per slave. The error in tracking the commanded internal force for objects with a high stiffness is less than 2 N (8%). The results prove the feasibility and effectiveness of the proposed method.

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