Cover Image

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Changhong, Lin, Jiarong, Sui, Zhiqiang, Qu, XiaoZhi, Wang, Rui, Sheng, Kehua, Zhang, Bo
Format:	Preprint
Published:	2025
Subjects:	Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
by: Hua, Zhihua, et al.
Published: (2026)

GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving
by: Liu, Shuai, et al.
Published: (2025)

Imitation Learning for Obstacle Avoidance Using End-to-End CNN-Based Sensor Fusion
by: Zain, Lamiaa H., et al.
Published: (2025)

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving
by: Oh, Haesung, et al.
Published: (2026)

FocalAD: Local Motion Planning for End-to-End Autonomous Driving
by: Sun, Bin, et al.
Published: (2025)

Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving
by: Lin, Haohong, et al.
Published: (2025)

End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning
by: Kishky, Mahmoud M., et al.
Published: (2024)

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios
by: Parada, Leandro, et al.
Published: (2024)

Integrating Decision-Making Into Differentiable Optimization Guided Learning for End-to-End Planning of Autonomous Vehicles
by: Liu, Wenru, et al.
Published: (2024)

Autonomous Vehicle Controllers From End-to-End Differentiable Simulation
by: Nachkov, Asen, et al.
Published: (2024)

A Physics-informed End-to-End Occupancy Framework for Motion Planning of Autonomous Vehicles
by: Shen, Shuqi, et al.
Published: (2025)

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

UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving
by: Song, Ziyi, et al.
Published: (2025)

Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
by: Song, Ziying, et al.
Published: (2025)

Learning Agile Swimming: An End-to-End Approach without CPGs
by: Lin, Xiaozhu, et al.
Published: (2024)

Learning-Based Leader Localization for Underwater Vehicles With Optical-Acoustic-Pressure Sensor Fusion
by: Yang, Mingyang, 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)

Prioritizing Perception-Guided Self-Supervision: A New Paradigm for Causal Modeling in End-to-End Autonomous Driving
by: Huang, Yi, et al.
Published: (2025)

DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Model
by: Yu, Rui, et al.
Published: (2025)

What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving
by: Zhou, Hongkuan, et al.
Published: (2023)

SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving
by: Zheng, Peiru, et al.
Published: (2025)

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
by: Liao, Bencheng, et al.
Published: (2024)

End-to-end Autonomous Vehicle Following System using Monocular Fisheye Camera
by: Zhang, Jiale, et al.
Published: (2025)

Exploring Contextual Representation and Multi-Modality for End-to-End Autonomous Driving
by: Azam, Shoaib, et al.
Published: (2022)

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
by: Jiang, Bo, et al.
Published: (2024)

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
by: Jiang, Bo, et al.
Published: (2024)

Enhancing End-to-End Autonomous Driving Systems Through Synchronized Human Behavior Data
by: Duan, Yiqun, et al.
Published: (2024)

GMF-Drive: Gated Mamba Fusion with Spatial-Aware BEV Representation for End-to-End Autonomous Driving
by: Wang, Jian, et al.
Published: (2025)

EgoPush: Learning End-to-End Egocentric Multi-Object Rearrangement for Mobile Robots
by: An, Boyuan, et al.
Published: (2026)

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
by: Feng, Renju, et al.
Published: (2025)

IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving
by: Zhang, Chenghao, et al.
Published: (2026)

UniSTPA: A Safety Analysis Framework for End-to-End Autonomous Driving
by: Kou, Hongrui, et al.
Published: (2025)

Exploring the Causality of End-to-End Autonomous Driving
by: Li, Jiankun, et al.
Published: (2024)

METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance
by: Guo, Ziang, et al.
Published: (2024)

FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving
by: Wang, Baoyun, et al.
Published: (2026)

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving
by: Liu, Haochen, et al.
Published: (2025)

End-to-End Generation of City-Scale Vectorized Maps by Crowdsourced Vehicles
by: Feng, Zebang, et al.
Published: (2025)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
by: Jiang, Hao, et al.
Published: (2025)

DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
by: Shang, Shuyao, et al.
Published: (2025)

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
by: Song, Ziying, et al.
Published: (2025)