Document Type
Conference Paper
Subject Area
CPS Model-Based Design, CPS Internet of Things, CPS Formal Methods
Date of this Version
4-15-2019
Publication Source
22nd ACM International Conference on Hybrid Systems: Computation and Control (HSCC), 2019
Abstract
In multi-agent systems, robots transmit their planned trajectories to each other or to a central controller, and each receiver plans its own actions by maximizing a measure of mission satisfaction. For missions expressed in temporal logic, the robustness function plays the role of satisfaction measure. Currently, a Piece-Wise Linear (PWL) or piece-wise constant reconstruction is used at the receiver. This allows an efficient robustness computation algorithm - a.k.a. monitoring - but is not adaptive to the signal class of interest, and does not leverage the compression properties of more general representations. When communication capacity is at a premium, this is a serious bottleneck. In this paper we first show that the robustness computation is significantly affected by how the continuous-time signal is reconstructed from the received samples, which can mean the difference between a successful control and a crash. We show that monitoring general spline-based reconstructions yields a smaller robustness error, and that it can be done with the same time complexity as monitoring the simpler PWL reconstructions. Thus robustness computation can now be adapted to the signal class of interest. We further show that the monitoring error is tightly upper-bounded by the L ∞ signal reconstruction error. We present a (non-linear) L ∞ -based scheme which yields even lower monitoring error than the spline-based schemes (which have the advantage of being faster to compute), and illustrate all results on two case studies. As an application of these results, we show how time-frequency specifications can be efficiently monitored online.
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Keywords
temporal logic, sampling, robustness, multi-agent, monitoring
Recommended Citation
Houssam Abbas, Yash Vardhan Pant, and Rahul Mangharam. 2019. Temporal Logic Robustness for General Signal Classes. In 22nd ACM International Conference on Hybrid Systems: Computation and Control (HSCC ’19), April 16–18, 2019, Montreal, QC, Canada. ACM, New York, NY, USA, Article 4, 12 pages. https://doi.org/10.1145/3302504.3311817
Bib Tex
@inproceedings{habbas19general,
author = {Abbas, Houssam and Pant, Yash Vardhan and Mangharam, Rahul},
title = {{Temporal Logic Robustness for General Signal Classes}},
booktitle = {22nd ACM International Conference on Hybrid Systems: Computation and Control},
series = {HSCC '19},
year = {2019},
publisher = {ACM},
keywords = {Temporal Logic, Sampling, Robustness, Multi-Agent, Monitoring}
}
Date Posted: 25 March 2019
This document has been peer reviewed.