Author

Xiao Li

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Preprint Aug 2026

NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments

This work presents NeuralParker, a reinforcement learning-based hybrid planner for arbitrary-pose parking that encodes full-environment obstacle and boundary geometry in a target-relative vertex representation, allowing the policy to retain route-defining context throughout the approach.

Zihan Wang, Baixiang Huang, Yang Guan et al. · 1 citation