Cover Image

PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Jie, Chen, Yingbing, Chen, Qifeng
Format:	Preprint
Published:	2024
Subjects:	Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RiskMap: A Unified Driving Context Representation for Autonomous Motion Planning in Urban Driving Environment
by: Xin, Ren, et al.
Published: (2024)

IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planning
by: Chen, Yingbing, et al.
Published: (2023)

Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictions
by: Wang, Sheng, et al.
Published: (2023)

PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
by: Chen, Zhili, et al.
Published: (2023)

PlanScope: Learning to Plan Within Decision Scope for Urban Autonomous Driving
by: Xin, Ren, et al.
Published: (2024)

PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning
by: Lin, Fangze, et al.
Published: (2024)

A Generic Trajectory Planning Method for Constrained All-Wheel-Steering Robots
by: Xin, Ren, et al.
Published: (2024)

Pushing the Limits of Reactive Planning: Learning to Escape Local Minima
by: Meijer, Isar, et al.
Published: (2024)

Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving
by: Huang, Zhiyu, et al.
Published: (2024)

DriveAnchor: Progressive Anchor-based Flow Learning for Autonomous Driving Planning
by: Yan, Limin, et al.
Published: (2026)

Beyond Imitation: A Life-long Policy Learning Framework for Path Tracking Control of Autonomous Driving
by: Gong, C., et al.
Published: (2024)

Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)
by: Li, Qifeng, et al.
Published: (2024)

Partial Motion Imitation for Learning Cart Pushing with Legged Manipulators
by: Das, Mili, et al.
Published: (2026)

Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
by: Zheng, Yupeng, et al.
Published: (2024)

Planning by Simulation: Motion Planning with Learning-based Parallel Scenario Prediction for Autonomous Driving
by: Niu, Tian, et al.
Published: (2024)

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
by: Wang, Junli, et al.
Published: (2026)

Imitation Learning for Autonomous Driving: Insights from Real-World Testing
by: Dursun, Hidayet Ersin, et al.
Published: (2025)

MRIC: Model-Based Reinforcement-Imitation Learning with Mixture-of-Codebooks for Autonomous Driving Simulation
by: He, Baotian, et al.
Published: (2024)

Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving
by: Chen, Zhili, et al.
Published: (2024)

CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving
by: Mirkhani, Hamidreza, et al.
Published: (2025)

LLM-Driven Scenario-Aware Planning for Autonomous Driving
by: Li, He, et al.
Published: (2026)

Bench2Drive-VL: Benchmarks for Closed-Loop Autonomous Driving with Vision-Language Models
by: Jia, Xiaosong, et al.
Published: (2026)

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving
by: Lian, Zhexi, et al.
Published: (2026)

Reinforced Imitative Trajectory Planning for Urban Automated Driving
by: Zeng, Di, et al.
Published: (2024)

CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving
by: Delavari, Elahe, et al.
Published: (2025)

Prompt, Plan, Perform: LLM-based Humanoid Control via Quantized Imitation Learning
by: Sun, Jingkai, et al.
Published: (2023)

IGDrivSim: A Benchmark for the Imitation Gap in Autonomous Driving
by: Grislain, Clémence, et al.
Published: (2024)

From Imitation to Exploration: End-to-end Autonomous Driving based on World Model
by: Li, Yueyuan, et al.
Published: (2024)

ZTRS: Zero-Imitation End-to-end Autonomous Driving with Trajectory Scoring
by: Li, Zhenxin, et al.
Published: (2025)

Computational Teaching for Driving via Multi-Task Imitation Learning
by: Gopinath, Deepak, et al.
Published: (2024)

CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
by: Zheng, Xiaoji, et al.
Published: (2025)

Neural Motion Simulator: Pushing the Limit of World Models in Reinforcement Learning
by: Hao, Chenjie, et al.
Published: (2025)

Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Driving
by: Langmann, Alexander, et al.
Published: (2025)

Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
by: Duan, Yiqun, et al.
Published: (2024)

Safe and Stylized Trajectory Planning for Autonomous Driving via Diffusion Model
by: Pei, Shuo, et al.
Published: (2026)

Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning
by: Zhang, Zhiwei, et al.
Published: (2025)

LHPF: Look back the History and Plan for the Future in Autonomous Driving
by: Wang, Sheng, et al.
Published: (2024)

Modified RRT* for Path Planning in Autonomous Driving
by: T, Sugirtha, et al.
Published: (2024)

DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Driving
by: Huang, Zhiyu, et al.
Published: (2023)

Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models
by: Chen, Jiao, et al.
Published: (2024)