Research On Kinematics And Trajectory Planning Of Power Tower Climbing Robot

With the wide application of robots in various fields,it is a future trend to use power tower climbing robot instead of manual inspection of power tower.Kinematics and trajectory planning of robots have always been the focus of research,and working accuracy and working efficiency are the key issues.Therefore,this paper takes Climbot as the research object,and carries out in-depth research from two aspects of kinematics and trajectory planning.Kinematics is the foundation of the research of multi-joint serial robot.In order to describe the position and attitude of the end of the Climbot robot,the improved D-H method was used to establish the connecting rod coordinate system.Then the forward and inverse kinematics equations were deduced and the accuracy was verified by the robot toolbox.At the same time,in order to prevent the target working point from being set in the dead zone,the working space of the robot was solved by using the Monte Carlo method based on the forward kinematics equation.A novel Adaptive Particle Swarm Optimization(IAPSO)algorithm was proposed to solve the problem of insufficient accuracy of inverse kinematics.The inverse kinematics problem is transformed into an optimal extremum problem with the aim of minimizing the distance between the desired pose and the target pose.Dynamic boundary and superboundary processing rules are used to ensure the uniqueness of the solution,and nonlinear inertia factor,population state judgment and adaptive learning factor are introduced to improve the accuracy of the solution.Experimental comparison results show that the inverse solution algorithm based on IAPSO improves the solution accuracy.According to the different requirements of different tasks on robot trajectories,the common trajectory planning methods of Cartesian space and joint space were studied and realized.In Cartesian space trajectory planning,the IAPSO algorithm proposed in this paper is used to map the dense interpolation points corresponding to the linear trajectory and arc trajectory to the joint angle changes in joint space,which verifies the reliability of IAPSO algorithm in continuous trajectory planning.In the trajectory planning of joint space,the single polynomial interpolation method and the mixed polynomial interpolation method are compared and analyzed,and the simulation shows that the performance of the trajectory curve obtained by the 5-3-5 mixed polynomial is better than other methods.In order to further improve the work efficiency of the robot on the basis of the5-3-5 hybrid polynomial,to join the robot kinematics constraints,regarding the shortest running time as the goal and using dual fitness function of genetic algorithm the optimal trajectory planning for robot.The simulation results show that the optimized joint movement time significantly shortened,trajectory planning efficiency improved.