Bounded Sub-optimal Multi-Robot Path Planning Using Satisfiability Modulo Theory (SMT) Approach

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00348042" target="_blank" >RIV/68407700:21240/20:00348042 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/IROS45743.2020.9341047" target="_blank" >https://doi.org/10.1109/IROS45743.2020.9341047</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS45743.2020.9341047" target="_blank" >10.1109/IROS45743.2020.9341047</a>

Result language

angličtina

Original language name

Bounded Sub-optimal Multi-Robot Path Planning Using Satisfiability Modulo Theory (SMT) Approach

Original language description

Multi-robot path planning (MRPP) is a task of planning collision free paths for a group of robots in a graph. Each robot starts in its individual starting vertex and its task is to reach a given goal vertex. Existing techniques for solving MRPP optimally under various objectives include search-based and compilation-based approaches. Often however finding an optimal solution is too difficult hence sub-optimal algorithms that trade-off the quality of solutions and the runtime have been devised. We suggest eSMT-CBS, a new bounded suboptimal algorithm built on top of recent compilation-based method for optimal MRPP based on satisfiability modulo theories (SMT). We compare eSMT-CBS with ECBS, a major representative of bounded sub-optimal search-based algorithms. The experimental evaluation shows significant advantage of eSMT-CBS across variety of scenarios.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA19-17966S" target="_blank" >GA19-17966S: intALG-MAPFg: Intelligent Algorithms for Generalized Variants of Multi-Agent Path Finding</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems

ISBN

978-1-7281-6212-6

ISSN

2153-0858

e-ISSN

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Number of pages

7

Pages from-to

11631-11637

Publisher name

IEEE Computer Society

Place of publication

Los Alamitos

Event location

Las Vegas

Event date

Oct 24, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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