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Lightweight Decentralized Neural Network-Based Strategies for Multi-Robot Patrolling

2024/12/16 by James Ward, Ward, James C., Ryan McConville +3 · 2 citations
Computer Science · Engineering · #Robotic Path Planning Algorithms #Modular Robots and Swarm Intelligence #Robot Manipulation and Learning

paper · pdf · doi:10.48550/arxiv.2412.11916

Abstract

The problem of decentralized multi-robot patrol has previously been approached primarily with hand-designed strategies for minimization of 'idlenes' over the vertices of a graph-structured environment. Here we present two lightweight neural network-based strategies to tackle this problem, and show that they significantly outperform existing strategies in both idleness minimization and against an intelligent intruder model, as well as presenting an examination of robustness to communication failure. Our results also indicate important considerations for future strategy design.

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