Multi-Agent Path Finding (MAPF) deals with finding collision free paths for a set of agents (robots) moving on a graph. The interest in MAPF in the research community started to increase recently partly due to practical applications in areas such as warehousing and computer games. However, the academic community focuses mostly on solving the abstract version of the problem (moving of agents on the graph) with only a few results on real robots. The presented software MAPF Scenario provides a tool for specifying MAPF problems on grid maps, solving the problems using various abstractions (for example, assuming rotation actions or not), simulating execution of plans, and translating the abstract plans to control programs for small robots Ozobots. The tool is intended as a research platform for evaluating abstract MAPF plans on real robots and as an educational and demonstration tool bridging the areas of artificial intelligence and robotics.

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.