Human Heuristics for a Team of Mobile Robots
Human Heuristics for a Team of Mobile Robots
复制标题
移动机器人团队的人类启发法
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Cédric Hartland
中科院分区：
文献类型：
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作者：
C. Tijus;E. Zibetti;V. Besson;Nicolas Bredèche;Y. Kodratoff;Mary Felkin;Cédric Hartland
这篇论文是在认知心理学和人工智能机器人学的十字路口。它报告了一个跨学科的项目，该项目关注在自主移动机器人中实施人类启发式。在下文中，我们解决了依靠基于人类的启发式算法来赋予一组移动机器人解决迷宫中的目标发现等问题的能力。这种启发式方法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方法有效的子任务。我们首先介绍了一组实验，这些实验是由一群寻找感知能力有限的目标的人类进行的。然后描述了从对它们行为的观察和分析中提取的启发式算法。最后，我们在Khepera类自主移动机器人中实现了这些启发式算法，这些机器人面临同样的任务。我们表明，控制体系结构可以在一定程度上得到实验验证，这要归功于这种方法。
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.