Complex safety study of intelligent multi-robot navigation in risk's environment

Chaima Bensaci, Y. Zennir, D. Pomorski, El-Arkam Mechhoud
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引用次数: 5

Abstract

The issue investigated in this paper concerns navigation, survey / control and the complexity associated with a mobile multi-robot coordination and cooperation in a complex environment (robotic analysis laboratory), which is little or no known with significant industrial risks, in the presence of human and machines. This group of mobile robots is mainly used to move chemical products, which can lead dangerous accidents (toxic, flammable, explosive …) between the different rooms of the laboratory. The objective of our study is to ensure a good precision in the robots navigation in order to optimize human efforts, reduced error and establishment safety while keeping an eye on robots with good functioning and a desired production. In the literature there are several risk analysis techniques. Among the most used techniques in robotics, the FMEA method (failure modes, effects and criticality analysis). We applied the FMEA method on one robot. Then, the FTA (Fault Tree Analysis) method was chosen to generalize dependability study on all robots. Finally, to manage this level of complexity, a control architecture based on controllers' decomposition into a set of elementary behaviors / controllers (obstacles avoidance and collision between robots, attraction to a target, planning …) was proposed.
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风险环境下智能多机器人导航的复杂安全性研究
本文研究的问题涉及导航、调查/控制以及在复杂环境(机器人分析实验室)中与移动多机器人协调和合作相关的复杂性,在人类和机器存在的情况下,这种环境很少或不知道有重大的工业风险。这组移动机器人主要用于在实验室不同房间之间移动可能导致危险事故(有毒、易燃、易爆…)的化学产品。我们的研究目的是确保机器人导航的良好精度,以优化人类的努力,减少错误和建立安全,同时保持机器人的良好功能和期望的生产。在文献中有几种风险分析技术。在机器人技术中最常用的技术是FMEA方法(失效模式,影响和临界分析)。我们将FMEA方法应用到一个机器人上。然后,采用故障树分析方法对所有机器人的可靠性研究进行推广。最后,为了管理这种复杂程度,提出了一种基于控制器分解为一组基本行为/控制器的控制体系结构(机器人之间的障碍物规避和碰撞、目标吸引、规划…)。
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