Intelligent Control System Of Trajectory Planning For A Welding Robot

Welding robot manipulator trajectory planning for industrial robots intelligent control has an important position.The trajectory planning of welding robot manipulator occupy an important position in the intelligent control of industrial robots.The traditional method used by welding manipulator is teaching-reproduction, once teached, the entire workflow process will follow it to weld, while such static model hardly achieve the high efficiency, low power requirements of industrial welding, on the other hand, manual optimization of welding trajectory is very difficult and hard to get this under automatic control. For this reason, in the process of welding robot manipulator repeatedly perform the same tasks, how to find a more efficient, less costly, and even the optimal trajectory through smart algorithms is the key point in the field of intelligent control of welding robot.In this thesis, the chip welding trajectory of manipulator was optimised from both the system energy and time. In the aspect of system energy, the Denavit-Hartenberg theory was used to achieve joint coordinates and Cartesian coordinate transformation, establish the motion equations, so to obtain effective self-learning capabilities of welding robot manipulator trajectory planning by setting some rules to meet the industry needs. In the aspect of time optimization, through the research of chip solder joints' distribution, the problem was transformed to the Hamilton circuit problem, improved genetic algorithm was used to obtaind optimal Hamilton circuit, so to optimise manipulator's welding trajectory. The effectiveness of improved genetic algorithm in the practical application of manipulator's chip welding was proved by the result of experiments.