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Mas-Based Pursuit-Evasion Algorithm Under Unknown Environment

机译:未知环境下基于Mas的追逃算法

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Based on the interaction protocols of Contract Net and Subscribe-publish, a distributive pursuit-evasion algorithm is proposed for multi-agents with limited detection ranges to pursue multi-evaders in an unknown grid map with obstacles. The pursuit agents first explore the map according to the method of Artificial Potential Field. When any obstacle is detected within the neighborhood of a pursuer, it updates the map. If an evader is detected, the pursuer (initiator) sends call-for-proposals messages to other pursuers. The other pursuers use D* algorithm to calculate their steps to reach the evader and submit their proposals. The initiator picks up the proposals and evaluates, chooses the nearest ones to join the pursuit team, sends accept-proposals to the selected agents and manages the team during the process of pursuit. If the evader is within the kill radius of all pursuit team members, the task is done; otherwise, D* algorithm is applied by each pursuit member to plan a new path once the evader moves to a new position. Distributive in nature, it allows a large-scale robot fleet to perform complicated tasks in a coordinated way. The algorithm can be easily extended to 3D cases. Simulation results show that the pursuit agents can dynamically form a pursuit team to catch evaders efficiently.
机译:基于Contract Net与Subscribe-publish的交互协议,针对检测范围有限的多智能体,提出了一种分布式追捕逃避算法,用于在未知的有障碍物的网格图中追捕多逃避者。追踪人员首先根据“人工势场”方法探索地图。当在追踪者附近检测到任何障碍物时,它会更新地图。如果检测到逃避者,则追踪者(发起者)将建议征集消息发送给其他追踪者。其他追踪者使用D *算法计算到达逃避者的步骤并提交提案。发起人挑选提案并进行评估,选择最接近的提案加入追踪小组,在选定的过程中向选定的代理发送接受提案并管理团队。如果逃避者在所有追踪团队成员的击杀半径内,则任务已完成;否则,任务已完成。否则,一旦逃避者移动到新位置,每个追踪成员就会应用D *算法来规划新路径。本质上是分布式的,它允许大型机器人机群以协调的方式执行复杂的任务。该算法可以轻松扩展到3D情况。仿真结果表明,追随者可以动态地组成一个追捕团队,以有效地躲避逃避者。

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