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

Aniketh Ramesh; Rustam Stolkin; Manolis Chiou

doi:10.1109/LRA.2022.3192612

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

Aniketh Ramesh, Rustam Stolkin, Manolis Chiou

Metallurgy and Materials

Research output: Contribution to journal › Letter › peer-review

Abstract

This letter addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots, in real-time, 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 lower-level metrics that estimate a variety of indicators of performance degradation faced by a robot at any given point in time. Robot health is a higher-level 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 for online estimation of robot performance degradation during run-time.

Original language	English
Pages (from-to)	10729-10736
Number of pages	8
Journal	IEEE Robotics and Automation Letters
Volume	7
Issue number	4
Early online date	20 Jul 2022
DOIs	https://doi.org/10.1109/LRA.2022.3192612
Publication status	Published - Oct 2022

Bibliographical note

Funding Information:
This work was supported by NCNR under Grants EP/R02572X/1, EP/P01366X/1, and EP/P017487/1, and in part by ReLiB under Grant FIRG005.

Publisher Copyright:
© 2016 IEEE.

Keywords

Failure detection and recovery
human-robot teaming
robotics in hazardous fields

ASJC Scopus subject areas

Control and Systems Engineering
Biomedical Engineering
Human-Computer Interaction
Mechanical Engineering
Computer Vision and Pattern Recognition
Computer Science Applications
Control and Optimization
Artificial Intelligence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/LRA.2022.3192612

ReLIB - Faraday Challenge Fast Track proposal - Circular economy
Elliott, R. (Co-Investigator), Lee, R. (Co-Investigator), Allan, P. (Co-Investigator), Slater, P. (Co-Investigator), Stolkin, R. (Co-Investigator), Walton, A. (Co-Investigator), Overton, T. (Co-Investigator), Reed, D. (Co-Investigator), Anderson, P. (Principal Investigator), Windridge, D. (Co-Investigator) & Gough, R. (Co-Investigator)
Engineering & Physical Science Research Council
1/03/18 → 30/06/21
Project: Research Councils
National Centre for Nuclear Robotics (NCNR)
Stolkin, R. (Principal Investigator), Leonardis, A. (Co-Investigator) & Stone, B. (Co-Investigator)
Engineering & Physical Science Research Council
2/10/17 → 1/04/22
Project: Research
Robust remote sensing for multi-modal characterisation in nuclear and other extreme environments
Leonardis, A. (Co-Investigator) & Stolkin, R. (Principal Investigator)
Engineering & Physical Science Research Council
1/05/17 → 1/11/21
Project: Research
Robotics for Nuclear Environments - Lead Manchester University (EP/P01366X/1)
Leonardis, A. (Co-Investigator) & Stolkin, R. (Principal Investigator)
Engineering & Physical Science Research Council
1/04/17 → 31/03/23
Project: Research

Cite this

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

abstract = "This letter addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots, in real-time, 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 lower-level metrics that estimate a variety of indicators of performance degradation faced by a robot at any given point in time. Robot health is a higher-level 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 for online estimation of robot performance degradation during run-time.",

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author = "Aniketh Ramesh and Rustam Stolkin and Manolis Chiou",

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AB - This letter addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots, in real-time, 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 lower-level metrics that estimate a variety of indicators of performance degradation faced by a robot at any given point in time. Robot health is a higher-level 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 for online estimation of robot performance degradation during run-time.

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Projects

ReLIB - Faraday Challenge Fast Track proposal - Circular economy

National Centre for Nuclear Robotics (NCNR)

Robust remote sensing for multi-modal characterisation in nuclear and other extreme environments

Robotics for Nuclear Environments - Lead Manchester University (EP/P01366X/1)

Cite this