Multi-Agent Path Finding on Ozobots
Multi-Agent Path Finding on Ozobots
Roman Barták, Ivan Krasičenko, Jiří Švancara
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Demos. Pages 6491-6493.
https://doi.org/10.24963/ijcai.2019/933
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.
Keywords:
AI: Multiagent Systems
AI: Planning and Scheduling
AI: AI Modelling and Simulation
Applications: Transport and logistics