Sparsification for Fast Optimal Multi-Robot Path Planning in Lazy Compilation Schemes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00356866" target="_blank" >RIV/68407700:21240/21:00356866 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/IROS51168.2021.9636296" target="_blank" >https://doi.org/10.1109/IROS51168.2021.9636296</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS51168.2021.9636296" target="_blank" >10.1109/IROS51168.2021.9636296</a>

Result language

angličtina

Original language name

Sparsification for Fast Optimal Multi-Robot Path Planning in Lazy Compilation Schemes

Original language description

Path planning for multiple robots (MRPP) represents a task of finding non-colliding paths for robots via which they can navigate from their initial positions to specified goal positions. The problem is often modeled using undirected graphs where robots move between vertices across edges while no two robots can simultaneously occupy the same vertex nor can traverse an edge in opposite directions. Contemporary optimal solving algorithms include dedicated search-based methods, that solve the problem directly, and compilation-based algorithms that reduce MRPP to a different formalism for which an efficient solver exists, such as constraint programming (CP), mixed integer linear programming (MILP), or Boolean satisfiability (SAT). In this paper, we enhance existing SAT-based algorithm for MRPP via sparsification of the set of candidate paths for each robot from which the target Boolean encoding is derived. Suggested sparsification of the set of paths led to a smaller target Boolean formulae that can be constructed and solved faster while optimality guarantees of the approach have been kept.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

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

2021

Confidentiality

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

Article name in the collection

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

ISBN

978-1-6654-1714-3

ISSN

2153-0858

e-ISSN

2153-0866

Number of pages

8

Pages from-to

7931-7938

Publisher name

IEEE

Place of publication

Piscataway

Event location

Praha

Event date

Sep 27, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000755125506042