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Double-robot obstacle avoidance path optimization for welding process
Author(s) -
Xuewu Wang,
Bin Tang,
Xin Zhou,
Xingsheng Gu
Publication year - 2019
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2019284
Subject(s) - obstacle avoidance , collision avoidance , motion planning , robot , obstacle , ant colony optimization algorithms , path (computing) , computer science , particle swarm optimization , process (computing) , mobile robot , mathematical optimization , simulation , collision , engineering , artificial intelligence , mathematics , algorithm , programming language , computer security , political science , law , operating system
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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