Inverse Kinematics Solution for Rope-Driven Continuum Robot Based on Gray Wolf Optimization Algorithm

Aiming at the difficult problem of solving the inverse kinematics of the continuous roped-driven manipulator, an efficient solution method based on the Grey Wolf Optimization Algorithm (GWO) is designed. The forward kinematic model of the robotic arm was established through the assumption of piecewise constant curvature. The mapping relationship from the joint space to the driving space was analyzed, and the inverse kinematic solution expression was derived through geometric methods, laying the foundation for the control of the continuous robotic arm. The inverse kinematics problem is transformed into an optimization problem by using the GWO algorithm. It is solved with the goals of minimizing the end pose error and optimizing the energy of joint Angle change, and a comparative analysis is conducted with the improved whale optimization algorithm. The simulation results show that the GWO algorithm has significant advantages in both solution accuracy and convergence speed, and can quickly obtain high-precision inverse solutions that meet the actual needs. This study verified the effectiveness and practicability of the GWO algorithm in solving complex nonlinear inverse kinematics problems.