摘要
移动作业机器人的作业任务往往有多个目标,针对每个作业目标,机器人的可停靠位置有无数个.如何在复杂环境和多作业目标约束下,对移动作业机器人进行合理的路径规划是一项难题.鉴于此,提出一种基于可操作度的移动作业机器人路径规划方法,在进行长度最优路径规划的同时,优化机械臂对目标作业的灵活性.首先,在节点采样阶段,研究机器人的可操作度在笛卡尔空间的分布,获取机器人在可停靠区域内对目标的可操作度;然后,采用高斯采样和梯度采样的方法在自由空间和移动机器人可停靠区域进行路径点采样,构建可操作度路线图;接着,在路径搜索阶段,对传统蚁群算法进行改进,提出适用于可操作度约束的启发式函数和局部最优预警策略;最后,在不同的仿真地图下对路径规划方法进行测试,验证了所提出方法在不同的环境下均有较高的适应能力,搜索出的路径代价较低,对目标的作业可操作度较高.
Mobile manipulators tasks frequently encompass multiple objectives.For each of these task objectives,there exist numerous potential docking positions.It is a challenge to conduct reasonable multi-targets path planning for mobile manipulators in complex environments.In this paper,we propose a multi-targets path planning method based on manipulability for mobile manipulators to optimize their flexibility while shorting paths lengths.During the node sampling,a study is conducted on the distribution of the robot’s manipulability in Cartesian space,allowing for the assessment of the robot’s manipulability with respect to the objectives within the docking area.The approach utilizes Gaussian sampling and gradient sampling methods to conduct path point sampling in both free space and the docking-eligible region of the mobile robot,thereby constructing an manipulability roadmap.During the path searching,this study introduces enhancements to the traditional ant colony algorithm by presenting heuristic functions suitable for manipulability constraints and a local-optimal warning strategy.Finally,the proposed path planning method is validated through tests on different simulated maps,showcasing its remarkable adaptability across diverse environments.The method consistently generates low-cost paths while ensuring a high level of manipulability.
作者
杨闰
李婧如
贾志昆
董二宝
YANG Run;LI Jing-ru;JIA Zhi-kun;DONG Er-bao(School of Engineering Science,University of Science and Technology of China,Hefei 230026,China;Institute of Advanced Technology,University of Science and Technology of China,Hefei 230022,China)
出处
《控制与决策》
EI
CSCD
北大核心
2024年第10期3243-3252,共10页
Control and Decision
基金
国家重点研发计划项目(2018YFB1307400)。
关键词
移动作业机器人
路径规划
多目标
可操作度
蚁群算法
mobile manipulator
path planning
multi-targets
manipulability
ant colony algorithm
