OzoMorph: Demonstrating Colored Multi-Agent Path Finding on Real Robots
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10439473" target="_blank" >RIV/00216208:11320/21:10439473 - isvavai.cz</a>
Result on the web
<a href="https://ojs.aaai.org/index.php/AAAI/article/view/17990/17795" target="_blank" >https://ojs.aaai.org/index.php/AAAI/article/view/17990/17795</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
OzoMorph: Demonstrating Colored Multi-Agent Path Finding on Real Robots
Original language description
Multi-agent Path Finding (MAPF) deals with finding collision-free paths for a set of agents on a graph, where each agent has its origin and destination. Colored MAPF is a generalization of MAPF, where groups of agents are moving, and the set of destination nodes is specified per group rather than per agent. OzoMorph is software providing an intuitive user interface for specifying Colored MAPF problems, solving them by translation to SAT, and finally visualizing the solution either in a computer simulation or by converting the plans to executable instructions for Ozobot Evo robots.
Czech name
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Czech description
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Classification
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)
Result continuities
Project
<a href="/en/project/GA19-02183S" target="_blank" >GA19-02183S: Smart Swarms: From Theory to Practice</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
ISBN
978-1-57735-866-4
ISSN
2159-5399
e-ISSN
2374-3468
Number of pages
3
Pages from-to
15991-15993
Publisher name
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE
Place of publication
PALO ALTO
Event location
Virtual, elektronicky
Event date
Feb 2, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000681269807191