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Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management

Authors :
Zhao, Xingyu
Osborne, Matt
Lantair, Jenny
Robu, Valentin
Flynn, David
Huang, Xiaowei
Fisher, Michael
Papacchini, Fabio
Ferrando, Angelo
Source :
Proceedings of 17th International Conference on Software Engineering and Formal Methods (SEFM 2019), Oslo, Norway (September 2019)
Publication Year :
2019

Abstract

The battery is a key component of autonomous robots. Its performance limits the robot's safety and reliability. Unlike liquid-fuel, a battery, as a chemical device, exhibits complicated features, including (i) capacity fade over successive recharges and (ii) increasing discharge rate as the state of charge (SOC) goes down for a given power demand. Existing formal verification studies of autonomous robots, when considering energy constraints, formalise the energy component in a generic manner such that the battery features are overlooked. In this paper, we model an unmanned aerial vehicle (UAV) inspection mission on a wind farm and via probabilistic model checking in PRISM show (i) how the battery features may affect the verification results significantly in practical cases; and (ii) how the battery features, together with dynamic environments and battery safety strategies, jointly affect the verification results. Potential solutions to explicitly integrate battery prognostics and health management (PHM) with formal verification of autonomous robots are also discussed to motivate future work.

Details

Database :
arXiv
Journal :
Proceedings of 17th International Conference on Software Engineering and Formal Methods (SEFM 2019), Oslo, Norway (September 2019)
Publication Type :
Report
Accession number :
edsarx.1909.03019
Document Type :
Working Paper
Full Text :
https://doi.org/10.1007/978-3-030-30446-1_6