A Hierarchical Conflict Resolution Method for Multi-Robot Path Planning

Abstract:

Multi-robot path planning using shared resources, easily conflict, prioritisation is the shared resource conflicts to resolve an important technology. This paper presents a learning classifier based on dynamic allocation of priority methods to improve the performance of the robot team. Individual robots learn to optimize their behaviors first, and then a high-level planner robot is introduced and trained to resolve conflicts by assigning priority. The novel approach is designed for Partially Observable Markov Decision Process environments. Simulation results show that the method used to solve the conflict in multi-robot path planning is effective and improve the capacity of multi-robot path planning.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 1482-1487
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.1482
• Online since: August 2013
• Authors: Jie Shao, Hai Xia Lin, Bin Song
• Keywords: Accuracy-Based Learning Classifier System (XCS), Genetic Algorithm (GA), Hierarchical Conflict, Multi-Robot, Path Planning

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