Multi-objective Trajectory Optimization Of Manipulator Based On Re-parameterization

In this paper,the five degree of freedom anthropomorphic manipulator developed by the research group and assembled and debugged by itself is taken as the research object,and the related problems involved in the trajectory planning of the multi degree of freedom manipulator are studied,mainly including the mathematical model establishment and kinematic dynamics analysis of the manipulator,the basic principle of trajectory planning,multi-objective genetic algorithm,simulation analysis,etc.,and new path and speed planning strategies are proposed Slightly.The main contents of this paper are as follows:Firstly,according to the structural parameters of the five DOF humanoid manipulator,the D-H parameter method is used to establish the mathematical model,and the forward and inverse kinematics analysis is carried out.The Lagrange method and Newton Euler method,which are commonly used in the dynamic analysis and calculation of the manipulator,are analyzed and compared.At the same time,the forward and inverse kinematics solutions and the inverse dynamics solutions of the manipulator are programmed.The program is verified by the robotics toolbox in MATLAB.Then,on the basis of kinematics and dynamics,the reachable workspace of the end of the manipulator is calculated and analyzed by Monte Carlo method.Then,it introduces the common joint space planning,Cartesian space planning and its related specific planning methods,as well as the related definition,calculation,global interpolation and local interpolation of non-uniform rational B-spline curve.In the process of path planning using spline local interpolation,the unit chord method is proposed to determine the direction of the vector at a given point to make the interpolation trajectory smoother.At the same time,the vector direction is adjusted as an optimization variable in the path planning,so as to change the shape of the path curve and search the fastest path of the trajectory.In order to ensure the high-order continuity of the trajectory curve,the high-order NURBS curve is used to replace the conventional velocity curve,and the global searching ability of genetic algorithm is fully utilized in the optimization solution to obtain the velocity curve which is highly suitable for the joint motion parameters and the end trajectory The conventional velocity curve can't adapt to the complex nonlinear relationship between the end track and joint motion parameters.Taking the three parameters of motion time,energy consumption and impact as the optimization objectives,the mechanical performance of the manipulator is taken as the constraint condition,according to the improved path interpolation algorithm and the strategy of re parameterized speed planning,the multi-objective optimization trajectory is planned for a given point,and the non dominated sorting genetic algorithm(NSGA-II)is used to search and solve,so as to obtain a good Pareto optimal solution set.The fitness of the optimal solution set is calculated and analyzed,and then the simulation model is established by using the SIM scape module of MATLAB to simulate the optimal fitness trajectory to verify the correctness and effectiveness of the algorithm.