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Non-Smooth Control Barrier Navigation Functions for STL Motion Planning
This paper reports on a new approach to Signal Temporal Logic (STL) control synthesis, that 1) utilizes a navigation function as the basis to construct a Control Barrier Function (CBF), and 2) composes navigation function-based barrier functions using nonsmooth mappings to encode Boolean operations...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044064/ https://www.ncbi.nlm.nih.gov/pubmed/35494541 http://dx.doi.org/10.3389/frobt.2022.782783 |
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author | Zehfroosh, Ashkan Tanner, Herbert G. |
author_facet | Zehfroosh, Ashkan Tanner, Herbert G. |
author_sort | Zehfroosh, Ashkan |
collection | PubMed |
description | This paper reports on a new approach to Signal Temporal Logic (STL) control synthesis, that 1) utilizes a navigation function as the basis to construct a Control Barrier Function (CBF), and 2) composes navigation function-based barrier functions using nonsmooth mappings to encode Boolean operations between the predicates that those barrier functions encode. Because of these two key features, the reported approach 1) covers a larger fragment of STL compared to existing approaches, 2) alleviates the computational cost associated with evaluation of the control law for the system in existing STL control barrier function methodologies, and 3) simultaneously relaxes some of the conservativeness of smooth combinations of barrier functions as a means of implementing Boolean operators. The paper demonstrates the efficacy of this new approach with three simulation case studies, one aiming at illustrating how complex STL motion planning specification can be realized, the second highlights the less-conservativeness of the approach in comparison to the existing methods, and another that shows how this technology can be brought to bear to push the envelope in the context of human-robot social interaction. |
format | Online Article Text |
id | pubmed-9044064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90440642022-04-28 Non-Smooth Control Barrier Navigation Functions for STL Motion Planning Zehfroosh, Ashkan Tanner, Herbert G. Front Robot AI Robotics and AI This paper reports on a new approach to Signal Temporal Logic (STL) control synthesis, that 1) utilizes a navigation function as the basis to construct a Control Barrier Function (CBF), and 2) composes navigation function-based barrier functions using nonsmooth mappings to encode Boolean operations between the predicates that those barrier functions encode. Because of these two key features, the reported approach 1) covers a larger fragment of STL compared to existing approaches, 2) alleviates the computational cost associated with evaluation of the control law for the system in existing STL control barrier function methodologies, and 3) simultaneously relaxes some of the conservativeness of smooth combinations of barrier functions as a means of implementing Boolean operators. The paper demonstrates the efficacy of this new approach with three simulation case studies, one aiming at illustrating how complex STL motion planning specification can be realized, the second highlights the less-conservativeness of the approach in comparison to the existing methods, and another that shows how this technology can be brought to bear to push the envelope in the context of human-robot social interaction. Frontiers Media S.A. 2022-04-13 /pmc/articles/PMC9044064/ /pubmed/35494541 http://dx.doi.org/10.3389/frobt.2022.782783 Text en Copyright © 2022 Zehfroosh and Tanner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Zehfroosh, Ashkan Tanner, Herbert G. Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title | Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title_full | Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title_fullStr | Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title_full_unstemmed | Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title_short | Non-Smooth Control Barrier Navigation Functions for STL Motion Planning |
title_sort | non-smooth control barrier navigation functions for stl motion planning |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044064/ https://www.ncbi.nlm.nih.gov/pubmed/35494541 http://dx.doi.org/10.3389/frobt.2022.782783 |
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