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Zonal RL-RRT: Hybrid Reinforcement Learning and RRT Approach to Path Planning
A new arXiv paper presents Zonal RL-RRT, a path-planning method that merges reinforcement learning with rapidly-exploring random trees. The approach divides the environment into zones to guide tree growth, aiming to cut planning time while keeping success rates and path costs reasonable. It targets navigation in cluttered, complex spaces where conventional planners struggle.