Double-robot obstacle avoidance path optimization for welding process

Xuewu Wang; Bin Tang; Xin Zhou; Xingsheng Gu; Xuewu Wang; Bin Tang; Xin Zhou; Xingsheng Gu

doi:10.3934/mbe.2019284

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 5: 5697-5708. doi: 10.3934/mbe.2019284

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Research article Special Issues

Double-robot obstacle avoidance path optimization for welding process

Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education,East China University of Science and Technology,Shanghai 200237, China

Received: 15 April 2019 Accepted: 16 May 2019 Published: 19 June 2019

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.
- welding robots,
- obstacle avoidance,
- path optimization,
- particle swarm optimization
Citation: Xuewu Wang, Bin Tang, Xin Zhou, Xingsheng Gu. Double-robot obstacle avoidance path optimization for welding process[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 5697-5708. doi: 10.3934/mbe.2019284

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Abstract

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.

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