Research On Path Planning Of The Body Side In White Welding Robot Based On Intelligent Algorithm

In order to meet the demand for the high rhythn,mass production and high efficient production,More and more robots were applied to the side body welding station.The engineering technicians were based on the experience of the path planning of the robot,Which often appeared that the production of the film was too long because of the unreasonable distribution of the task,and affected the beat because of robot interference,Therefore,it was very important to study the path planning problem of this robot to en sure safety production and product quality and shorten the working time of welding.By analyzing the advantages and disadvantages of particle swarm optimization and genetic algorithm in solving the problem of single robot path optimization,A new hybrid particle swarm algorithm was proposed to fuse the advantages of the two algorithms.A TSP Problem Model with Constrained Constraints for Path Optimization was built.Taking the side of the assembly welding station on a robot welding path for the optimization of the object for example,In MATLAB,respectively,the preparation of genetic algorithms and hybrid particle swarm algorithm to achieve path optimization procedures,Through the comparative analysis of the two simulation results showed the rationality and superiority of the hybrid particle swarm algorithm.In order to solve the shortcomings of genetic algorithm in solving multi-robot path optimization problem,A new algorithm-multi-population genetic algorithm was proposed,Genetic algorithms were applied in parallel to multiple subpopulations.The multi-robot path planning problem was transformed into the problem of solder joint distribution with constraints and the problem of single robot path optimization and the corresponding mathematical model was built.Taking a Case Study on the Path Planning of Two Welding Robots on the Body Side in White for example,Path planning procedures were respectively by means of genetic algorithms and multi-population genetic algorithmon the platfrom of MATLAB.Through the comparison between the two simulation results we can see,The new algorithm had the characteristics of stability,fast convergence and strong ability of searching,the planning result of which was closer to production practice.