Applying MAPP Algorithm for Cooperative Path Finding in Urban Environments

2017/07/20 by Anton Andreychuk, Andreychuk, Anton, Konstantin Yakovlev +1
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Modular Robots and Swarm Intelligence #Multiagent Systems (cs.MA) #Robotic Path Planning Algorithms #cs.AI #cs.MA

paper · pdf · doi:10.48550/arxiv.1707.06607

arxiv created 2017/07/20 · openalex publication_date 2017/07/20 · arxiv updated 2017/07/21 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28

Abstract

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.

Related

• Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas
• Decentralised Approach for Multi Agent Path Finding
• Path Finding for the Coalition of Co-operative Agents Acting in the Environment with Destructible Obstacles
• Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding
• Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios