Back to Search Start Over

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

Authors :
Jennifer Lantair
Xingyu Zhao
Valentin Robu
Matthew Osborne
Xiaowei Huang
David Flynn
Michael J. Fisher
Fabio Papacchini
Angelo Ferrando
Source :
Software Engineering and Formal Methods ISBN: 9783030304454, SOFTWARE ENGINEERING AND FORMAL METHODS (SEFM 2019)
Publication Year :
2019
Publisher :
Springer International Publishing, 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

ISBN :
978-3-030-30445-4
ISBNs :
9783030304454
Database :
OpenAIRE
Journal :
Software Engineering and Formal Methods ISBN: 9783030304454, SOFTWARE ENGINEERING AND FORMAL METHODS (SEFM 2019)
Accession number :
edsair.doi.dedup.....8b5960d0033caeb76e19da96334c7088
Full Text :
https://doi.org/10.1007/978-3-030-30446-1_6