Home /Research /Multi-objective path optimization for arc welding robot based on discrete DN multi-objective particle swarm optimization
SWARM

Multi-objective path optimization for arc welding robot based on discrete DN multi-objective particle swarm optimization

Xuewu Wang, Xingsheng Gu

Year
2019
Citations
7
Access
Open access

Abstract

Rational weld seams sequence is important for improving welding productivity and quality. Hence, intelligent path optimization strategy is introduced to obtain optimized weld seams sequence in this article. The path length and total welding deformation are considered for multi-objective path planning. First, the optimization problem description is presented. At the same time, the path length and the total welding deformation of some sequences are calculated. Then, improved multi-objective particle swarm optimization algorithm is studied. In addition, the agent model is obtained based on the sample data and experiment design. At last, the proposed algorithm is applied to optimize the welding path length and total welding deformation. The simulation results show the effectiveness of the optimization strategy.

Keywords

WeldingComputer sciencePath (computing)Particle swarm optimizationSwarm behaviourRobot weldingMathematical optimizationSequence (biology)MetaheuristicAlgorithm

Related papers

Browse all SWARM papers