Human Heuristics for a Team of Mobile Robots

C. Tijus, E. Zibetti, V. Besson, Nicolas Bredèche, Y. Kodratoff, Mary Felkin, Cédric Hartland
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引用次数: 4

Abstract

This paper is at the crossroad of cognitive psychology and AI robotics. It reports a cross-disciplinary project concerned about implementing human heuristics within autonomous mobile robots. In the following, we address the problem of relying on human-based heuristics to endow a group of mobile robots with the ability to solve problems such as target finding in a labyrinth. Such heuristics may provide an efficient way to explore the environment and to decompose a complex problem into subtasks for which specific heuristics are efficient. We first present a set of experiments conducted with group of humans looking for a target with limited sensing capabilities solving. Then we describe the heuristics extracted from the observation and analysis of their behavior. Finally we implemented these heuristics within khepera-like autonomous mobile robots facing the same tasks. We show that the control architecture can be experimentally validated to some extent thanks to this approach.
移动机器人团队的人类启发式
本文正处于认知心理学和人工智能机器人的十字路口。它报告了一个跨学科项目,关注在自主移动机器人中实现人类启发式。在下面,我们解决了依靠基于人的启发式来赋予一组移动机器人解决迷宫中寻找目标等问题的能力的问题。这种启发式可以提供一种有效的方法来探索环境,并将复杂问题分解为特定启发式有效的子任务。我们首先提出了一组实验进行了一组人类寻找目标有限的传感能力解决。然后,我们描述了从观察和分析他们的行为中提取的启发式。最后,我们在面对相同任务的类似khepera的自主移动机器人中实现了这些启发式算法。我们表明,由于这种方法,控制体系结构可以在一定程度上得到实验验证。
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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