基于改进ACO的机器人路径规划与仿真研究
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摘要
焊接机器人是自动化焊接制造中必不可少的部分。目前,国内大多依靠人的经验对机器人路径进行规划,后期需要反复调试,造成工作量的增加。针对这一问题,提出一种改进的蚁群算法,给出在焊接过程中无干扰、最短时间的路径。通过在ROBCAD中进行焊接仿真实验,并考虑机器人的可达性和干涉问题,最后计算出仿真时间。研究结果表明:改进的ACO算法对焊接效率和焊接时间有一定的改善,为进一步研究机器人焊接路径规划提供了参考。
Welding robot is a vital part of automatic welding process. At present, in domestic, robot path planning relies on human experience mostly. Repeated debug is needed later, resulting in increased workload. To solve this problem, an improved ACO algorithm was proposed, and a path with the least interference and the shortest time in the welding process was given. The welding simulation experiment was performed in ROBCAD, considering the accessibility and interference problem of the robot. Lastly the simulation time was calculated. The improved ACO algorithm has improved the welding efficiency and welding time, which provides reference for further study of robot welding path.
Welding robot is a vital part of automatic welding process. At present, in domestic, robot path planning relies on human experience mostly. Repeated debug is needed later, resulting in increased workload. To solve this problem, an improved ACO algorithm was proposed, and a path with the least interference and the shortest time in the welding process was given. The welding simulation experiment was performed in ROBCAD, considering the accessibility and interference problem of the robot. Lastly the simulation time was calculated. The improved ACO algorithm has improved the welding efficiency and welding time, which provides reference for further study of robot welding path.
引文
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[7]毕志强.工业机器人协调运动规划与研究[D].广州:华南理工大学,2014.
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[10]田延硕.遗传算法的研究与应用[D].成都:电子科技大学,2004.