摘要
超冗余度机器人具有大量自由度,且任务的多样性以及偏大的行动空间均导致其路径规划难度较高、耗时较长。为此,提出考虑障碍避让的超冗余度机器人路径规划方法。基于信息熵方法,建立超冗余度机器人工作环境栅格地图,获取环境中障碍物位置,确定目标栅格,生成初始路径;采用A^(*)算法优化路径节点序列,结合动态切点调整算法对节点平滑处理,根据建立的代价函数,规划出全局路径;引入人工势场方法,将机器人、目标与障碍物三者之间相对速度关系作为优化路径的指标,实时优化机器人行进路径,规划局部路径。实验结果表明,利用上述方法规划机器人路径时,规划时间短且路径较短。
Super redundant robots have a large number of degrees of freedom,and the diversity of tasks and large action space make their path planning difficult and time-consuming.Therefore,a path planning method for a hyperredundant robot considering obstacle avoidance was proposed.Based on the information entropy,the grid map of the working environment of hyper-redundant robot was established,so that the location of obstacles in the environment can be obtained.The target grid was determined,whereupon the initial path was generated.Moreover,A^(*)algorithm was used to optimize the sequence of path nodes,and the dynamic point cut adjustment algorithm was used to smooth the nodes.According to the cost function,the global path was planned.Finally,the artificial potential field method was introduced,and the relative velocity relationship among robot,target and obstacle was taken as the index of path optimization to optimize the robot path in real time and plan the local path.The experimental results show that this method needs less robot path planning time and shorter path.
作者
赵鹏
李昆
程杰
ZHAO Peng;LI Kun;CHENG Jie(College of Information Science and Technology,Yanching Institute of Technology,Langfang Hebei 065201,China;College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China)
出处
《计算机仿真》
北大核心
2023年第12期487-491,共5页
Computer Simulation
关键词
超冗余度机器人
路径规划方法
环境地图建立
人工势场方法
Hyper-redundant robot
Path planning method
Establishment of green-map
A^(*)algorithm
Artificial potential field
