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Multi-robot path planning for smart access of distributed charging points in map

机译:多机器人路径规划,用于MAP中分布式充电点的智能访问

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摘要

Autonomous mobile robots are being used to automate many tasks such as cleaning, delivering items, and surveillance. Such tasks often require uninterrupted and continuous service. However, robots have limited battery power and must be recharged frequently. Since manually charging each robot is not always feasible, automatic charging (docking) stations have been developed to automate the process of charging. In a multi-robot system, the tasks are generally distributed between the robots, and different robots have different amounts of remaining battery power. Since the charging stations are expensive, a limited number of charging points are generally available. Hence, an intelligent planner to manage a limited number of charging points for a large number of robots is essential. In this work, we propose a multi-robot path planner for intelligently accessing a limited number of charging points distributed on the map. Unlike traditional path planners, which mainly consider the shortest path criterion to generate paths, the proposed planner also considers the remaining battery power of the robots, task priority, and robot's location in the map. It allocates the most appropriate charging station to the robots, which require recharging. Simulation results show that the proposed planner can reduce trajectory re-planning, and plan efficient paths to the available charging points.
机译:自主移动机器人正在用于自动化许多任务,例如清洁,提供物品和监视。这些任务通常需要不间断和连续的服务。但是,机器人电池电量有限,必须经常充电。由于手动充电每个机器人并不总是可行的,因此已经开发了自动充电(对接)站来自动化充电过程。在多机器人系统中,任务通常分布在机器人之间,不同的机器人具有不同量的剩余电池功率。由于充电站是昂贵的,通常可以获得有限数量的充电点。因此,一个智能规划师来管理大量机器人数量的有限数量的充电点是必不可少的。在这项工作中,我们提出了一种多机器人路径规划器,用于智能地访问分布在地图上的有限数量的充电点。与传统路径规划者不同,这主要考虑最短的路径标准来生成路径,所提出的计划人员还考虑了机器人,任务优先级和机器人位置的剩余电池电量。它将最合适的充电站分配给机器人,需要充电。仿真结果表明,拟议的计划人员可以减少轨迹重新计划,并计划可用充电点的有效路径。

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