关键词: 车身, 焊装工艺, 任务分配, 多机器人, 智能优化

Abstract: The task allocation and process planning for the multi-station &multi-robots in the spot welding process are key issues for the assembly efficiency.This problem involves complicated sub-problems such as multi-station and multi-robot hierarchical task allocation,single-robot spot welding sequence planning,and multi-robot collaboration in single station.It is a highly coupled optimization problem with complex engineering constraints.Traditional task allocation methods are often solved by step-by-step optimization,and it is difficult to obtain optimal task planning results in a multi-station multi-robot system.To address this problem,considering multiple constraints such as robot reachability,collision detection,welding cycle time within the station and multi-robot consistency,a comprehensive optimization model was constructed for the Multi-Station Multi-Robot Task Allocation (MS-MRTA) problem.Furthermore,an improved self-organizing neural network and a cyclic optimization strategy were proposed for optimal task allocation of MS-MRTA problem.To evaluate the effectiveness of the proposed method,a body side assembly case was used for comparative analysis with different state-of-art task allocation methods.Results showed that the multi-station assembly cycle was reduced by 14.49% on average based on the proposed algorithm,and the consistency of multiple robots in the stations was also improved by 54.22% on average.

Key words: auto body, spot welding, task allocation, multi-robot, intelligent optimization