未知环境下多机器人协作追捕算法

Multi-Robot Cooperative Pursuit Algorithm for in An Unknown Environment

研究了在未知环境下一种多机器人协作追捕多个移动目标方法,将追捕过程分为环境地图创建、构建追捕团队,及团队成员协作快速捕获目标三部分.设计抽象传感器模型用于追捕者探索障碍物.综合考虑与捕获目标相关的各种因素建立属性关系样本数据集,提出了利用关联规则数据挖掘技术构建追捕团队的方法.通过对追捕目标位置预测,将追捕问题类比为多机器人协作路径规划问题,在环境地图基础上求解追捕团队到达目标位置的最优路径.仿真结果表明,多机器人能够高效地协作捕获移动目标,证明了所提方法在复杂动态环境下实现的可行性及有效性.

An approach of cooperative hunting for multiple mobile targets by multi-robot is presented in an unknown environment,which divides the pursuit process into creating the environment map,forming the pursuiting teams and capturing the targets.The abstract sensor model is designed to search obstacles for hunters.The data sets of attribute relationship is built by consulting all of factors about capturing evaders,then the association rule data mining is used to build the pursuit groups.Through doping out the positions of targets,the puisuit game can be transformed into multi-robot path planning problems.The best path can be found in the environment map.The simulation results show that the mobile evaders can be captured effectively and efficiently,and prove the feasibility and validity of the given algorithm under dynamic environment.