论文标题

机器人生命力和机器人健康:在不利条件下机器人中有系统地量化运行时性能降解

Robot Vitals and Robot Health: Towards Systematically Quantifying Runtime Performance Degradation in Robots Under Adverse Conditions

论文作者

Ramesh, Aniketh, Stolkin, Rustam, Chiou, Manolis

论文摘要

本文解决了任务执行过程中远程移动机器人中自动检测和量化性能退化的问题。在执行任务期间,机器人可能会遇到各种不确定性和逆境,这可能会损害其有效执行任务并导致其绩效降解的能力。可以通过及时的检测和干预来缓解或避免这种情况(例如,由远程人类主管接管在远程流动模式下的控制)。受到医院中患者分类系统的启发,我们介绍了“机器人生命力”的框架,以估算整体“机器人健康”。机器人的生命值是一组指标,可以估计机器人在给定时间点面临的性能降解程度。机器人健康是一种将机器人生命力结合到性能降解的单个标量值估计值中的度量。在模拟和实际移动机器人中,实验表明,可以有效地使用提出的机器人生命力和机器人健康来估计运行时机器人性能降解。

This paper addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots during task execution. A robot may encounter a variety of uncertainties and adversities during task execution, which can impair its ability to carry out tasks effectively and cause its performance to degrade. Such situations can be mitigated or averted by timely detection and intervention (e.g., by a remote human supervisor taking over control in teleoperation mode). Inspired by patient triaging systems in hospitals, we introduce the framework of "robot vitals" for estimating overall "robot health". A robot's vitals are a set of indicators that estimate the extent of performance degradation faced by a robot at a given point in time. Robot health is a metric that combines robot vitals into a single scalar value estimate of performance degradation. Experiments, both in simulation and on a real mobile robot, demonstrate that the proposed robot vitals and robot health can be used effectively to estimate robot performance degradation during runtime.

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