Environment-Specific Route-Library Adaptation for Decentralized Multi-Robot Navigation via Hybrid RRT and Behavior Cloning in Grid-Based Industrial Environments
This work studies a hybrid framework pairing an offline Rapidly-Exploring Random Tree expert with a Behavior Cloning local policy and route reuse, evaluated in a reproducible simulator, and results are a quantitative analysis of environment-specific route-library adaptation.