An Approach for Safeguarding Autonomous Mobile Robots Using Monitoring Tools

Manuel Müller, Natalie Schinzel, N. Jazdi, M. Weyrich
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引用次数: 1

Abstract

Autonomous mobile robots with manipulators are becoming increasingly important in industry because they are the most flexible type of mobile robots. Therefore, these mobile robots are employed in dynamic, heterogeneous and partly structured environments. However, as depicted in ANSI/RIA R15.08-1-2020, new safety requirements focusing the fitness of the mobile robots to its operational scenarios arise. In contrast to fenced industrial robots, mobile robots need to reason about their environment, specifically the monitored space and adapt accordingly. However, since the monitored space is often limited, today’s autonomous industrial mobile robots type C (IMR-C) as R15.08-1-2020 names this kind of robots waste much potential reducing their pace of work due to limited monitored space. To counteract this issue, we first analyze the effects of limited monitored space using system theoretic process analysis (STPA) and then come up with a novel monitoring tool closing the blind spots of the IMR-Cs. The comparison of the STPAs with and without external monitoring tools show risk reduction in the original loss scenarios but new loss scenarios and consuming effort in order to assemble them. We present a methodology to weight the gains and losses of assembling an additional monitoring tool using the Digital Twin. The evaluation of our prototype in a goods receipt scenario shows promising results.
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使用监控工具保护自主移动机器人的方法
具有操纵臂的自主移动机器人是最灵活的移动机器人类型,在工业中越来越重要。因此,这些移动机器人被应用于动态、异构和部分结构化的环境中。然而,正如ANSI/RIA R15.08-1-2020所描述的那样,新的安全要求集中在移动机器人对其操作场景的适应性上。与围栏工业机器人相比,移动机器人需要对其环境进行推理,特别是被监控的空间,并相应地进行适应。然而,由于监控空间往往是有限的,今天的自主工业移动机器人C型(IMR-C)作为R15.08-1-2020命名这类机器人浪费了很多潜力,降低了他们的工作速度,由于有限的监控空间。为了解决这个问题,我们首先使用系统理论过程分析(STPA)分析了有限监测空间的影响,然后提出了一种新的监测工具,关闭了IMR-Cs的盲点。有外部监测工具和没有外部监测工具的技术指标方案的比较表明,原始损失情景的风险降低了,但新的损失情景的风险降低了,组装这些情景需要耗费大量的精力。我们提出了一种方法来权衡使用数字孪生组合额外监测工具的得失。在货物收货场景中对我们的原型进行了评估,结果令人鼓舞。
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