Research On Collision-free Path And Trajectory Optimization Of Welding Robot Based On Virtual Simulation

With the improvement of the intelligent level of industrial production lines,welding robots are widely used to improve production efficiency.In the actual production process,the welding robot not only needs to complete a large number of welding spot welding tasks,but also needs to improve production efficiency as much as possible,reduce energy consumption,and run smoothly.Therefore,this article takes the welding robot as the research object,and conducts an in-depth study on the optimal trajectory of the welding robot passing a given path point.Firstly,the side structure of the body-in-white and the influence objects of welding robot path planning are studied,and the influence of manufacturing resources,spot welding technology and overall layout of resources on the motion planning of welding robots is analyzed.Based on the digital factory software Process Designer,the process planning of the side wall welding line of the white body was carried out,the initial welding point welding sequence was obtained,and the kinematics analysis of the welding robot was carried out in combination with the actual parameters.The kinematics model of the welding robot was established in MATLAB according to the DH parameters.,Using MATLAB Robotic Toolbox to complete the forward and inverse kinematics solution,which provides the necessary theoretical support for the trajectory optimization of the welding robot.Secondly,using the shortest welding path of the welding robot as the starting point,the path planning problem of the welding robot is classified as a TSP problem,and the ant colony algorithm is introduced.Through a large number of simulation experiments,the values of various parameters with better optimization ability in the algorithm are obtained.At the same time,in view of the shortcomings of ant colony algorithm such as slow convergence speed and easy to fall into local optimal solutions,the pheromone update strategy and dynamic random disturbance strategy are introduced to improve the algorithm,and the improved ant colony algorithm is simulated and verified.The simulation results are compared with the simulation results of the basic ant colony algorithm and the ant colony algorithm introducing a single improvement strategy,which proves the feasibility and effectiveness of the improved ant colony algorithm,and provides the shortest welding path for the subsequent optimization of the welding robot trajectory.Thirdly,on the basis of the shortest welding path of the welding robot,that is,based on the given path point,the time optimal trajectory planning of the welding robot is carried out.Using the characteristics of the B-spline curve,the cubic B-spline interpolation method is selected for the trajectory planning of the welding robot.,The joint angle,angular velocity and angular acceleration curves of the welding robot obtained by the simulation are continuous and smooth.Under the kinematics constraints,the trajectory interpolation time is optimized by the improved genetic algorithm.The simulation result shows that the optimal running time of the welding robot is 96.3s,The optimization efficiency has reached 25%,and the trajectory diagram of each joint of the welding robot at the optimal time is constructed using the cubic B-spline interpolation method.The simulation graphics show that the motion trajectory of all joints is stable and continuous,which realizes the optimal time of the welding robot Trajectory planning.Fourthly,the multi-objective optimization function with the shortest welding time and the least energy consumption is established,and the NSGA-Ⅱ algorithm is used to solve the multi-objective optimization trajectory of the welding robot.A penalty function is introduced in the algorithm to deal with the kinematic constraints of the welding robot,and the multi-objective function model Converted to an unconstrained multi-objective function model,and established the fitness function required by the algorithm.The simulation obtained the Pareto optimal solution set.According to the welding task requirements,one set of optimized solutions was selected,and the results were compared with the time optimal algorithm results.In comparison,the multi-objective optimization algorithm reduces the running time of the welding robot while also reducing its energy consumption.Finally,on the basis of the process planning of the welding production line constructed by Process Designer,the digital factory simulation software Process Simulate is used to build a virtual simulation experiment platform for welding robots spot welding side parts of the body in white,establish the motion model of the manufacturing resources,and define the welding For the welding task of the robot,the optimal trajectory planned by the algorithm was simulated and verified,and a solution was proposed for the collision and interference problem that appeared in the simulation.Finally,a collision-free welding path was obtained.By analyzing the motion curves of the joints of the welding robot under the path and The simulation timing diagram before and after the trajectory optimization shows that the optimization algorithm planning the welding robot trajectory has guiding significance for the actual processing,and is conducive to further optimizing the efficiency of the actual production on the spot.