Optimization of the Stewart Platform Based on Improved Genetic Optimization

Based on the improved genetic optimization, a new Stewart platform optimization design method is proposed in this paper. Through introducing chaotic mapping and simulation annealing strategy, combining the kinematic analysis of the Stewart platform and the constraint conditions of the workspace, aiming at maximizing the workspace and minimizing the motion error, the structural parameters of the platform are optimized. The experimental results show that the improved GA significantly improves the workspace and motion performance of the Stewart platform compared with the traditional ant colony optimization and basic genetic optimization.