Research On Joint Space Trajectory Planning Of Excavator

The research on the trajectory planning of excavator is an important part of its intelligent development and has great significance.In this paper,RIPPA PC1012 small hydraulic excavator is taken as the research object,and the optimal trajectory planning of the excavator manipulator arm is studied with time and pulse as the performance indexes,so as to improve the efficiency of the excavator in the actual excavation work and reduce the impact on the joint in the process of work.Firstly,the standard D-H method is used to establish the connecting rod coordinate system of the excavator and its kinematics analysis is carried out.Monte Carlo method was used to obtain the working space range of the excavating robot,and a reasonable working area was selected to set the excavation path points.Using geometric method to solve the inverse kinematics,compared with the analytical method,the solution is more simple.Secondly,cubic,Quintic,Seventh degree non-uniform B-spline curve and piece-wise quintic polynomial curve interpolation were used to carry out the trajectory planning of the excavator robot in joint space,and the trajectory planning method of the dynamic characteristic indexes and bucket tooth tip trajectory were analyzed,compared with the same order of polynomial curve,B spline curve with local support and calculation more simple.Then,under the constraints of angular velocity,angular acceleration and pulsation at each joint,non-uniform B-spline curves of different orders were used to interpolate the discrete angle points of the joint,Taking the shortest joint action time as the optimization objective,the particle swarm optimization algorithm was adopted to optimize the solution,and the optimization results under different orders of non-uniform B-spline curves were compared and analyzed.Finally,the optimization of joint running time and pulse synthesis was taken as the objective function,and the quintic nonuniform B-spline was taken as the interpolation curve.The improved adaptive mutation particle swarm optimization algorithm(AMPSO)was used to optimize the objective function,the results show that the motion trajectory obtained by this method can reduce the impact on each joint in the process of motion with less motion time.The feasibility and effectiveness of this method are verified.