This is the authors' abstract. We don't add key points for this paper.
For path planning of two welding robots, intelligent robot path optimization with obstacle avoidance is introduced first, where the optimization objective is the shortest time. In the optimization process, grid method is used for modeling. Then, ant colony algorithm is applied as search strategy to realize obstacle avoidance between welding gun and workpiece. For obstacle avoidance of robot joints, the robot is modeled using the sphere and the capsule. Besides, two-level collision detection and geometrical collision avoidance are used to obtain collision free robots' path. At last, an improved particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the proposed strategy could improve the effectiveness of the path planning. It can be used to shorten the teaching time and strengthen offline programming ability.
No takes yet. Share an insight, caveat, or question.
Wang et al. (2019) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: