arXiv Machine Learning
NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments
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Drive As You Like: Multi-Head Diffusion with Reinforcement Learning for Personalized Driving
arXiv:2508. 16947v2 Announce Type: replace-cross Abstract: Despite significant progress, imitation learning-based autonomous driving planners remain largely restricted to reproducing high-frequency biased behaviors, overlooking the inherent behavioral diversity of human driving.
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ConsistencyPlanner: Real-time Planning with Fast-Sampling Consistency Models
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ParkingTransformer: LLM-Enhanced End-to-End Trajectory Planning for Autonomous Parking
arXiv:2606. 17082v1 Announce Type: cross Abstract: End-to-end autonomous parking has emerged as a critical task within the realm of autonomous driving.
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From Semantic Decisions to Feasible Trajectories: Self-Evolving LLM-Guided Optimal Control for Narrow-Space Parking
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Hugging Face Trending Papers
Sep 21
From Semantic Decisions to Feasible Trajectories: Self-Evolving LLM-Guided Optimal Control for Narrow-Space Parking
Autonomous parking in nonconvex and narrow environments remains challenging. Although optimal-control methods can explicitly enforce vehicle dynamics and collision constraints, nonconvexity compromise...