A cooperative exploration strategy with efficient backtracking for mobile robots

Jinho Kim, Stephanie Bonadies, Andrew Lee, S. Gadsden
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引用次数: 7

Abstract

This paper proposes a cooperative robot exploration (CREI strategy which is based on the sensor-based random tree (SKT) method. The proposed CRE strategy is for exploring unknown environments with a team of mobile robots equipped with range finder sensors. An existing backtracking technique for frontier-based exploration involves moving back through inefficient routes. To enhance the efficiency of the backtracking algorithm, a hub node is defined and the most direct backtracking route is generated using its frontier data. Numerical simulations demonstrate that the proposed strategy enables exploration of unknown environments by robots more efficiently than other common methods.
移动机器人高效回溯的协同探索策略
提出了一种基于传感器随机树(SKT)方法的协同机器人探索(CREI)策略。提出的CRE策略是用一组配备测距传感器的移动机器人探索未知环境。现有的基于边界的勘探回溯技术涉及通过低效的路线返回。为了提高回溯算法的效率,定义了一个集线器节点,并利用其边界数据生成最直接的回溯路径。数值模拟结果表明,该策略比其他常用方法更有效地实现了机器人对未知环境的探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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