摘要
在复杂多变的工作环境,特别是在多丘陵等特殊地理位置,快速选择最优路径,避开障碍物,完成作业,需要进行采摘机器人的路径规划。基于改进蚁群算法对拣选机器人路径进行规划,搜索效率较低,存在早熟收敛的可能,基于此,提出基于人工智能算法的采摘机器人最优路径规划方法。构建环境模型,为减少初始寻路时间,提高搜索速度,增强全局优化能力,全面查看搜索路径上的当前节点、下一个节点和目标节点,增加路径选择的多样性,提高收敛速度,实现采摘机器人最优路径规划。实验结果表明,设计方法能有效地解决特殊地理环境下,采摘机器人拾取器的最优避障规划问题,具有较高的效率和优越性。
In the complex and changeable working environment,especially in special geographical locations such as hills,it is necessary to plan the path of the picking robot,so that it can quickly select the optimal path,avoid obstacles and complete the operation.The path planning of picking robot based on improved ant colony algorithm has low search efficiency and has the possibility of premature convergence.In view of this,an optimal path planning method for picking robot based on artificial intelligence algorithm was proposed.The environment model was constructed to reduce the initial pathfinding time,improve the search speed,enhance the global optimization ability,comprehensively view the current node,next node and target node on the search path,increase the diversity of path selection,improve the convergence speed,and realize the optimal path planning of the picking robot.The experimental results show that the design method can effectively solve the optimal obstacle avoidance planning problem of picking robot pickup in special geographical environment,and has high efficiency and superiority.
作者
翟睿
ZHAI Rui(School of Mathematics and Big Data,Anhui University of Science and Technology,Huainan 232001,China)
出处
《成都工业学院学报》
2022年第1期52-54,共3页
Journal of Chengdu Technological University
关键词
人工智能算法
采摘机器人
最优路径规划
安全避障
环境模型
收敛速度
artificial intelligence algorithm
picking robot
optimal path planning
safe obstacle avoidance
environmental model
convergence rate
作者简介
翟睿(1992-),男,在读硕士研究生,研究方向:分布式优化、机器学习,电子邮箱:827029766@qq.com。
