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Open AccessArticle

Welding Robot Collision-Free Path Optimization

Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
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Appl. Sci. 2017, 7(2), 89; https://doi.org/10.3390/app7020089
Received: 10 November 2016 / Accepted: 11 January 2017 / Published: 8 February 2017
(This article belongs to the Special Issue Gas Tungsten Arc Welding)
Reasonable welding path has a significant impact on welding efficiency, and a collision-free path should be considered first in the process of welding robot path planning. The shortest path length is considered as an optimization objective, and obstacle avoidance is considered as the constraint condition in this paper. First, a grid method is used as a modeling method after the optimization objective is analyzed. For local collision-free path planning, an ant colony algorithm is selected as the search strategy. Then, to overcome the shortcomings of the ant colony algorithm, a secondary optimization is presented to improve the optimization performance. Finally, the particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the desired welding path can be obtained based on the optimization strategy. View Full-Text
Keywords: welding robot; path planning; collision-free; ant colony algorithm; particle swarm optimization algorithm welding robot; path planning; collision-free; ant colony algorithm; particle swarm optimization algorithm
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MDPI and ACS Style

Wang, X.; Xue, L.; Yan, Y.; Gu, X. Welding Robot Collision-Free Path Optimization. Appl. Sci. 2017, 7, 89.

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