Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education,East China University of Science and Technology,Shanghai 200237, China.
Math Biosci Eng. 2019 Jun 19;16(5):5697-5708. doi: 10.3934/mbe.2019284.
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.
针对两个焊接机器人的路径规划问题，首先引入了具有避障功能的智能机器人路径优化方法，优化目标是最短时间。在优化过程中，采用栅格法进行建模。然后，应用蚁群算法作为搜索策略，实现焊接枪与工件之间的避障。对于机器人关节的避障，使用球体和胶囊对机器人进行建模。此外，采用两级碰撞检测和几何避障方法来获得无碰撞的机器人路径。最后，采用改进的粒子群优化算法实现全局路径规划。仿真结果表明，所提出的策略可以提高路径规划的有效性。它可以用于缩短示教时间，增强离线编程能力。
