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Area of Science:

  • Robotics
  • Control Systems
  • Space Engineering

Background:

  • Space manipulators with flexible joints present control challenges due to complex dynamics.
  • Existing visual servo algorithms may lack certainty in intermediate states, increasing collision risks.

Purpose of the Study:

  • To introduce a novel high-certainty visual servo algorithm for space manipulators with flexible joints.
  • To enhance both kinematic and dynamic certainty for safer and more precise operations.
  • To reduce the risk of collision by improving intermediate state control.

Main Methods:

  • A three-stage motion planner in Cartesian space to control intermediate states and minimize position error.
  • A joint space planner using fast gradient descent to optimize joint deviation from centrality.
  • A Lyapunov dynamics model reference adaptive controller for enhanced anti-disturbance capability.

Main Results:

  • Experimental validation demonstrated consistency between visual servo motion and planned states.
  • Average joint deviation from centrality was less than 40%.
  • Motion trajectory consistency exceeded 90% under various inertial load disturbances.

Conclusions:

  • The proposed algorithm enhances the certainty of position-based visual servo (PBVS) methods.
  • It effectively reduces collision risks in space manipulator operations.
  • The method offers improved precision and robustness in dynamic environments.