An Improved Gray Wolf Optimization Algorithm Based on Tent Chaotic Initialization and Differential Evolution Strategy for Space Robot Base Attitude Undisturbed Planning

When the space robot contacts with the target, due to the coupling between the manipulator and the base, the instantaneous impulse generated at the end may cause a large roll of the base. This paper proposes a new base attitude undisturbed planning algorithm. Firstly, the dynamic equation of the space robot based on the variable stiffness joint is established . Secondly, using Tent chaotic map, differential evolution strategy and nonlinear control parameter strategy to improve the grey wolf optimization algorithm, an improved gray wolf optimization algorithm based on Tent chaotic initialization and differential evolution strategy is constructed. The stiffness value of variable stiffness joint is used as the gray wolf individual, and the algorithm is applied to the base attitude undisturbed planning of the space robot. Finally, the simulation results show that the algorithm can achieve base attitude undisturbed planning very well.