Research On Dynamic Multi-objective Optimization Of Motion Posture Of Humanoid Robot

Humanoid robots can assist or replace humans in various jobs because of their similar shape and structure.In recent years,humanoid robots are mostly used in toys,performances,education and other service industries,but it is difficult to get large-scale application in actual production operations.One of the reasons is that compared with other robots,the structure of humanoid robots is more complex,its performance is difficult to get efficient and reasonable application,resulting in low efficiency and high cost.The motion posture of humanoid robot walking can be divided into gait planning and path planning.Gait planning determines the speed,stability and motor cost of the walking operation,and path planning determines the length and safety of the walking path.These performances restrict each other and cannot optimize all performances.This is a multi-objective optimization problem.In order to achieve performance optimization on the basis of balancing various performances,an improved dynamic multi-objective optimization algorithm is proposed to optimize the performance of humanoid robots during walking operation.The research contents are divided into three parts:(1)An improved dynamic multi-objective optimization algorithm is proposed,and its adaptability,real-time performance and reliability are verified by test experiments.(2)The walking speed,walking stability and motor cost performance of the humanoid robot are summarized as objective functions,and the objective function is substituted into the improved dynamic multi-objective optimization algorithm to realize the optimization of gait planning of the humanoid robot,which is verified by experiments.(3)Multi-objective path planning of robot based on artificial potential field(APF)method can solve the problem that traditional APF method is easy to fall into zero potential field under complex obstacles and can not guarantee the optimal path.The optimal balance between the shortest path and the safest path is achieved through experiments,and the path planning of humanoid robot is completed.