Applying MAPP Algorithm for Cooperative Path Finding in Urban Environments
This addresses path planning for mobile robots like UAVs in complex settings, but appears incremental as it applies an existing decentralized method to a specific scenario.
The paper tackled the problem of planning non-conflict trajectories for dozens of UAVs in urban environments using the MAPP algorithm, and results showed it is highly efficient for such tasks.
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.