The paper considers the problem of planning a set of non-conflict trajectories for the coalition of intelligent agents (mobile robots). Two divergent approaches, e.g. centralized and decentralized, are surveyed and analyzed. Decentralized planner - MAPP is described and applied to the task of finding trajectories for dozens UAVs performing nap-of-the-earth flight in urban environments. Results of the experimental studies provide an opportunity to claim that MAPP is a highly efficient planner for solving considered types of tasks.
@article{arxiv.1707.06607,
title = {Applying MAPP Algorithm for Cooperative Path Finding in Urban Environments},
author = {Anton Andreychuk and Konstantin Yakovlev},
journal= {arXiv preprint arXiv:1707.06607},
year = {2017}
}