The Multi-objective Optimizatioin Of Welding Manipulator Trajectory

Industrial robots have been starting since the early 1960 s, experienced nearly 50 years of development, now it has been widely used in industrial field and it has become the main electromechanical integration equipment in the high automatic manufacture field, which is the most widely used is mechanical arm. The main purpose of using the application of the mechanical arm is to reduce the number of the staff, improve labor productivity, and at the same time of reducing labor intensity to improve the quality of products. There are two main advantages which compared with the use of mechanical arm and the use of traditional machines: first, it is easy to realize the fully automated in the production process; and the second is the highly adaptive capacity of production equipment. The development of new industrial robot is a hot spot in current research areas. Based on Motoman robot K6(arm) as the research object, research on its six degrees of freedom under the condition of path, time and energy optimization problem. First of all, Motoman robot kinematics model is established, and the trajectory of the motion is studied. Regard shortest path, the shortest time and energy as the optimization objective, to explore the optimal trajectory of the robot. Thesis mainly finished the following work:1, According to the structural parameters of K6 Motoman robot welding manipulator, the robot kinematics model is established by D-H method, and the analysis of the forward and inverse kinematics of the robot is carried out;2, Respectively, analyze the connecting rods and joints of robot trajectory planning method in Cartesian space. Using the three degree polynomial method to realize the trajectory planning of the robot in the space of any point to the target point in the joint motion control;3, Through the welding robot working space, with shortest path as the optimization goal, genetic algorithm is used to implement the shortest path planning, and comparing with simulation annealing algorithm.4, According to the path obtained above, the running time is established to fit the function, and regard the shortest time as the optimization goal, then get the speed continuous, the shortest time of the robot controlling program;5, On the basis of above the path and time obtained above, regard the minimum kinetic energy as the optimization goal, directly get the optimal path of robot kinetic energy between two nodes.6, Based on the path, the shortest time, the lowest energy as the optimization objective, using the methods of multi-objective algorithm NSGA-II and PSO particle swarm algorithm, So as to accomplish the optimization of the trajectory of the welding manipulator.