{"type":"ScholarlyArticle","title":"Multi-Agent Path Finding on Ozobots","authors":[{"name":"Roman Barták","slug":"roman-bartak","given":"Roman","family":"Barták","affiliation":"Charles University , Faculty of Mathematics and Physics , Czech Republic"},{"name":"Ivan Krasičenko","slug":"ivan-krasicenko","given":"Ivan","family":"Krasičenko","affiliation":"Charles University , Faculty of Mathematics and Physics , Czech Republic"},{"name":"Jiří Švancara","slug":"jiri-svancara","given":"Jiří","family":"Švancara","affiliation":"Charles University , Faculty of Mathematics and Physics , Czech Republic"}],"abstract":"Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (mobile robots) moving on a graph. There exists several abstract models describing the problem with various types of constraints. The demo presents software to evaluate the abstract models when the plans are executed on Ozobots, small mobile robots developed for teaching programming. The software allows users to design the grid-like maps, to specify initial and goal locations of robots, to generate plans using various abstract models implemented in the Picat programming language, to simulate and to visualise execution of these plans, and to translate the plans to command sequences for Ozobots.","doi":"10.24963/ijcai.2019/933","url":"https://ijcai.org/proceedings/2019/933","pdf":"https://ijcai.org/proceedings/2019/0933.pdf","markdown":"https://ijcai.org/proceedings/2019/933.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/933","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Demos","track":"Demos","number":933,"pages":{"first":6491,"last":6493},"keywords":["Applications: Transport and logistics","AI: Multiagent Systems","AI: Planning and Scheduling","AI: AI Modelling and Simulation"],"videos":[],"references":[{"position":1,"raw":"[Atzmon et al., 2018] Dor Atzmon, Roni Stern, Ariel Felner, Glenn Wagner, Roman Barták, and Neng-Fa Zhou. Robust multi-agent path finding. In Proceedings of the 17th Inter- national Conference on Autonomous Agents and MultiA- gent Systems (AAMAS), pages 1862-1864, 2018.","title":"Robust multi-agent path finding","authors":"Dor Atzmon, Roni Stern, Ariel Felner, Glenn Wagner, Roman Barták, Neng-Fa Zhou","year":"2018","venue":"Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Barták et al., 2017] Roman Barták, Neng-Fa Zhou, Roni Stern, Eli Boyarski, and Pavel Surynek. Modeling and solving the multi-agent pathfinding problem in picat. In 29th IEEE International Conference on Tools with Artifi- cial Intelligence, ICTAI 2017, pages 959-966. IEEE Com- puter Society, 2017.","title":"Modeling and solving the multi-agent pathfinding problem in picat","authors":"Barták","year":"2017","venue":"29th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2017","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Barták et al., 2018a] Roman Barták, Jiří Švancara, and Marek Vlk. A scheduling-based approach to multi- agent path finding with weighted and capacitated arcs. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pages 748-756, 2018.","title":"Roman Barták, Jiří Švancara, and Marek Vlk. A scheduling-based approach to multiagent path finding with weighted and capacitated arcs","authors":"Barták","year":"2018","venue":"Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Barták et al., 2018b] Roman Barták, Jiří Švancara, Věra Škopková, and David Nohejl. Multi-agent path finding on real robots: First experience with ozobots. In Advances in Artificial Intelligence -IBERAMIA 2018 -16th Ibero- American Conference on AI, pages 290-301, Cham, 2018. Springer.","title":"Roman Barták, Jiří Švancara, Věra Škopková, and David Nohejl. Multi-agent path finding on real robots: First experience with ozobots","authors":"Barták","year":"2018","venue":"Advances in Artificial Intelligence -IBERAMIA 2018 -16th Ibero-American Conference on AI","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Felner et al., 2017] Ariel Felner, Roni Stern, Solomon Eyal Shimony, Eli Boyarski, Meir Goldenberg, Guni Sharon, Nathan R. Sturtevant, Glenn Wagner, and Pavel Surynek. Search-based optimal solvers for the multi-agent pathfind- ing problem: Summary and challenges. In The Interna- tional Symposium on Combinatorial Search (SoCS), pages 29-37, Palo Alto, 2017. AAAI Press.","title":"Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges","authors":"Ariel Felner, Roni Stern, Solomon Eyal Shimony, Eli Boyarski, Meir Goldenberg, Guni Sharon, Nathan R Sturtevant, Glenn Wagner, Pavel Surynek","year":"2017","venue":"The International Symposium on Combinatorial Search (SoCS)","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Ross and Ryan, 2008] Malcolm Ross and Kinsella Ryan. Exploiting subgraph structure in multi-robot path plan- ning. J. Artif. Intell. Res., 31:497-542, 2008.","title":"Exploiting subgraph structure in multi-robot path planning","authors":"Malcolm Ross, Kinsella Ryan","year":"2008","venue":"J. Artif. Intell. Res","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Russell and Norvig, 2009] Stuart J. Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. Pren- tice Hall, 2009.","title":"Artificial Intelligence: A Modern Approach","authors":"Stuart J Russell, Peter Norvig","year":"2009","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}