An efficient robotic exploration planner with probabilistic guarantees
An efficient robotic exploration planner with probabilistic guarantees
复制标题
具有概率保证的高效机器人探索规划器
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
M. Campbell
中科院分区：
文献类型：
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作者：
Alexander Ivanov;M. Campbell
机器人在未知、传感器有限、全球信息缺乏的环境中进行有效探索，对路径规划算法提出了独特的挑战，因为无法对路径完成和任务成功做出确定性保证。集成勘探（IE），努力结合定位和勘探，必须解决，以创造一个自主的机器人系统，能够在新的和具有挑战性的环境中长期运行。本文提出了一个概率框架，该框架允许创建提供成功概率保证的探索算法。在哈密顿路径问题和探索之间建立了一种新的联系。针对IE问题，开发了保证概率信息资源管理器（G-PIE），提供了路径完成的概率保证和探索的渐近最优性。
Efficient robotic exploration of an unknown, sensor limited, global-information-deficient environment poses a unique challenge to path planning algorithms because no deterministic guarantees on path completion and mission success can be made. Integrated Exploration (IE), which strives to combine localization and exploration, must be solved in order to create an autonomous robotic system capable of long term operation in new and challenging environments. This paper formulates a probabilistic framework which allows the creation of exploration algorithms providing probabilistic guarantees of success. A novel connection is made between the Hamiltonian Path Problem and exploration. The Guaranteed Probabilistic Information Explorer (G-PIE) is developed for the IE problem, providing a probabilistic guarantee on path completion, and asymptotic optimality of exploration.