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Multi-objective Exploration and Search for Autonomous Rescue Robots

机译:自主救援机器人的多目标探索与搜索

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"Exploration and search" is a typical task for autonomous robots performing in rescue missions, specifically addressing the problem of exploring the environment and at the same time searching for interesting features within the environment. In this paper, we model this problem as a multi-objective exploration and search problem and present a prototype system, featuring a strategic level, which can be used to adapt the task of exploration and search to specific rescue missions. Specifically, we make use of high-level representation of the robot plans through a Petri Net formalism that allows representing in a coherent framework decisions, loops, interrupts due to unexpected events or action failures, concurrent actions, and action synchronization. While autonomous exploration has been investigated in the past, we specifically focus on the problem of searching interesting features in the environment during the map building process. We discuss performance evaluation of exploration and search strategies for rescue robots, by using an effective performance metric, and present evaluation of our system through a set of experiments.
机译:“探索与搜索”是执行救援任务的自主机器人的典型任务,特别是解决探索环境并同时在环境中搜索有趣特征的问题。在本文中,我们将此问题建模为一个多目标的探索和搜索问题,并提出了一个具有战略水平的原型系统,该系统可用于使探索和搜索任务适应特定的救援任务。具体来说,我们通过Petri Net形式主义利用机器人计划的高级表示形式,该形式形式允许在一致的框架中表示决策,循环,由于意外事件或动作失败引起的中断,并发动作以及动作同步。尽管过去已经研究了自主探索,但我们特别关注在地图构建过程中搜索环境中有趣特征的问题。我们使用有效的性能指标来讨论救援机器人的探索和搜索策略的性能评估,并通过一组实验对我们的系统进行评估。

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