Step-length optimization based on genetic algorithm for a parallel mobile robot

With the development of technology, parallel mobile robots have been paid more attention in various industries due to the strong load capacity, high running stability and rapid response speed. However, step-length optimization is an important but challenging task for this kind of mobile robot. Step length has dramatic effect on the stability of robot and the performance of electric cylinder. Balancing the speed characteristics and stability margin, we propose a genetic algorithm to solve this problem and design a novel fitness function that can measure the motion characteristics of parallel mobile robot. Effectiveness of our method is verified by experiments.