Trajectory planning of the robotic arm using improved grey wolf algorithm

Abstract

Robotic arm technology plays a crucial role in various fields such as automated production and intelligent manufacturing. However, challenges remain in achieving high precision, high speed, and complex smooth trajectory planning. This paper focuses on a six - degree - of - freedom robotic arm, conducting kinematic forward and analytical inverse solutions, and subsequently proposes a 5-5 polynomial interpolation planning algorithm based on an improved Grey Wolf Optimization (IGWO) algorithm. The improved Grey Wolf Optimization algorithm enhances the convergence factor and introduces a probability perturbation strategy to optimize the interpolation time of each segment, aiming for the optimal operation time of the robotic arm. Simulation results show that, compared to traditional Grey Wolf Optimization and Particle Swarm Optimization algorithms, the improved Grey Wolf Optimization algorithm has faster iteration speed and superior global search capabilities, ensuring smooth operation of the robotic arm with continuous, smooth, and non - mutational position, velocity, and acceleration at each joint.