Abstract
The problem of cooperative path-finding is addressed in this work. A set of agents moving in a certain environment is given.
Each agent need to reach a given goal location. The task is to find spatial temporal paths for agents such that they eventually reach their goals by following these paths without colliding with each other.
An abstraction where the environment is modeled as an undirected graph is adopted - vertices represent locations and edges represent passable regions. Agents are modeled as elements placed in the vertices.
Space occupancy by agents is represented by a constraint that at most one agent can be located in a vertex at a time. At least one vertex remains unoccupied to allow agents to move.
An agent can move into unoccupied neighboring vertex or into a vertex being currently vacated in a certain case. Two novel scalable algorithms for solving cooperative path-finding in bi connected graphs are presented.
They are both targeted on the case with environments densely populated by agents which is the case that has now yet been addressed fully in the literature. It has been shown theoretically and experimentally that presented algorithms outperform existent algorithms capable of solving the given class in terms of speed as well as in terms of quality of generated solutions.