Motion Planning Technology Research Of Industrial Robots For Complex Curved Surface Polishing

With the development of the intelligent manufacturing industry,the machining of complex curved parts gradually replaces the traditional manual operation with the robot.How to improve the performance of robot and its service life is an important issue of robot optimization trajectory planning at present.Based on the experimental platform,Route Planing Algorithms,path optimization algorithm and the simulation result,a study on optimal trajectory planning of machining of complex surface with robot is reported.Firstly,the paper takes the door handle as the research object,and according to the technological requirements of the polishing of the door handles,we design a flexible belt-polishing platform with constant grinding presure and supporting equipments.The kinematics model of the robot's belt-polishing workstation is established by using the D-H method.Secondly,the paper discusses the common tool path planning methods,and analyzes their advantages and disadvantages.Also,this paper sums up the section path planning method based on curvature.On account of the cross section path planing of the curvature,we propose a algorithm about belt polishing with robot based on external dynaminc TCP.By calculating the surface information of the Gaussian curvature and mean curvature of the complex curved surface,according to the flexible profile of the sand belt,the TCP points with different regions of the surface parts are automatically selected according to the external dynamic TCP algorithm,and then the path planning trajectory of the complex surface is obtained.Thirdly,upon satisfying the constraints,the particle swarm algorithm is improvede,taking the total energy of particle as the object function.In this paper,the particle is initialized by the normal distribution of energy dissipation,the energy dissipation is calculated by multiplying the constraint conflict degree coefficient and the inertia factor,and by dividing the maximum value by the inertia factor,the vector with the least power dissipation is calculated,and finally the trajectory of the robotmotion is generated.Finally,It's about the simulation and experiment.We take the door handle as the experiment object,using the normalized particle swarm optimization algorithm to optimize the trajectory,and the result is satisfactory.Through the comparison of standrad particle swarm's energy consumption and the optimized changing paramenter curve of robots.It was found that the trajectory optmization has advantages of good smoothing,and it can reduce the energy consumption of robots.