自动驾驶

Multi-Modal Sensor Fusion using Hybrid Attention for Autonomous Driving

多模态传感器融合使用混合注意力用于自动驾驶

Mayank Mayank, Bharanidhar Duraisamy, Florian Geiß, Abhinav Valada

机构 * Mercedes-Benz AG（梅赛德斯-奔驰集团） ； University of Freiburg（弗莱堡大学） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；BEV(abstract)；分类 cs.CV

AI总结 本文提出MMF-BEV框架，通过变形注意力实现雷达与摄像头BEV融合，通过传感器贡献分析验证传感器互补性，并在VoD数据集上优于单模态基线。

Comments 9 pages, 8 figures

Boreas Road Trip: A Multi-Sensor Autonomous Driving Dataset on Challenging Roads

Boreas Road Trip：一个针对挑战性道路的多传感器自动驾驶数据集

Daniil Lisus, Katya M. Papais, Cedric Le Gentil, Elliot Preston-Krebs, Andrew Lambert, Keith Y. K. Leung, Timothy D. Barfoot

机构 * University of Toronto Institute of Aerospace Studies（多伦多大学航空航天研究学院） ； Trimble（Trimble公司） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.RO

AI总结 Boreas Road Trip数据集通过多传感器数据评估自动驾驶算法在挑战性道路条件下的性能。

Comments 23 pages, 15 figures, 12 tables, submitted to The International Journal of Robotics Research (IJRR)

EKF-Based Fusion of Wi-Fi/LiDAR/IMU for Indoor Localization and Navigation

Zeyi Li, Zhe Tang, Kyeong Soo Kim, Sihao Li, Jeremy S. Smith

机构 * School of Advanced Technology, Xi'an Jiaotong-Liverpool University（西安交通大学利物浦大学先进技术学院） ； Department of Electrical Engineering and Electronics, University of Liverpool（利物浦大学电子工程系） ； Zhejiang University of Technology（浙江工业大学） ； School of Artificial Intelligence, Suzhou Vocational Institute of Industrial Technology（苏州工业职业技术学院人工智能学院） 纠错

专题命中 多传感器融合 ：LiDAR(title,abstract)；occupancy(abstract)；分类 cs.RO

Comments 8 pages, 7 figures, 3 tables, and submitted for presentation at a conference

RadarSplat: Radar Gaussian Splatting for High-Fidelity Data Synthesis and 3D Reconstruction of Autonomous Driving Scenes

Pou-Chun Kung, Skanda Harisha, Ram Vasudevan, Aline Eid, Katherine A. Skinner

机构 * University of Michigan（密歇根大学） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.CV

DriveAgent: Multi-Agent Structured Reasoning with LLM and Multimodal Sensor Fusion for Autonomous Driving

Xinmeng Hou, Wuqi Wang, Long Yang, Hao Lin, Jinglun Feng, Haigen Min, Xiangmo Zhao

机构 * Chang’an University（长安大学） ； Agency for Science, Technology and Research (A*STAR)（科技研究局） ； University of California, Davis（加州大学戴维斯分校） ； CCNY Robotics Lab, The City College of New York（纽约城市学院机器人实验室） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.RO

DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic Fusion

Haoteng Li, Zhao Yang, Zezhong Qian, Gongpeng Zhao, Yuqi Huang, Jun Yu, Huazheng Zhou, Longjun Liu

机构 * National Key Laboratory of Human-Machine Hybrid Augmented Intelligence（国家级人机混合增强智能实验室） ； National Engineering Research Center for Visual Information and Applications（国家视觉信息与应用工程研究中心） ； Institute of Artificial Intelligence and Robotics（人工智能与机器人研究所） ； Xi’an Jiaotong University（西安交通大学） ； University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 多传感器融合 ：autonomous driving(title)；BEV(abstract)；occupancy(abstract)；分类 cs.CV

Comments 8 pages, 6 figures,

Testing the Fault-Tolerance of Multi-Sensor Fusion Perception in Autonomous Driving Systems

Haoxiang Tian, Wenqiang Ding, Xingshuo Han, Guoquan Wu, An Guo, Junqi Zhang. Wei Chen, Jun Wei, Tianwei Zhang

机构 * Institute of Software Chinese Academy of Sciences（中国科学院软件研究所） ； Nanyang Technological University（南洋理工大学） ； University of CAS, Nanjing（中国科学院大学南京分校） ； Nanjing Institute of Software Technology, University of CAS, Nanjing（中国科学院南京软件技术研究所） ； Continental-NTU Corporate Lab（Continental-NTU企业实验室） ； University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.RO

LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion

Guoliang You, Xiaomeng Chu, Yifan Duan, Xingchen Li, Sha Zhang, Jianmin Ji, Yanyong Zhang

专题命中 多传感器融合 ：LiDAR(title,abstract)；autonomous driving(abstract)；分类 cs.CV

Comments 8 pages

OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction

Ji Zhang, Yiran Ding, Zixin Liu

专题命中 多传感器融合 ：occupancy(title,abstract)；autonomous driving(abstract)；分类 cs.CV

PseudoCal: Towards Initialisation-Free Deep Learning-Based Camera-LiDAR Self-Calibration

Mathieu Cocheteux, Julien Moreau, Franck Davoine

专题命中 多传感器融合 ：LiDAR(title,abstract)；self-driving(abstract)；分类 cs.CV

Comments British Machine Vision Conference (BMVC) 2023

Journal ref BMVC 2023: 829-831

Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers

James Gunn, Zygmunt Lenyk, Anuj Sharma, Andrea Donati, Alexandru Buburuzan, John Redford, Romain Mueller

专题命中 多传感器融合 ：LiDAR(title,abstract)；autonomous driving(abstract)；分类 cs.CV

Comments Updated method figure; camera ready

MaskFuser: Masked Fusion of Joint Multi-Modal Tokenization for End-to-End Autonomous Driving

Yiqun Duan, Xianda Guo, Zheng Zhu, Zhen Wang, Yu-Kai Wang, Chin-Teng Lin

专题命中 多传感器融合 ：autonomous driving(title)；BEV(abstract)；LiDAR(abstract)；分类 cs.CV

4D Millimeter-Wave Radar in Autonomous Driving: A Survey

Zeyu Han, Jiahao Wang, Zikun Xu, Shuocheng Yang, Lei He, Shaobing Xu, Jianqiang Wang, Keqiang Li

专题命中 多传感器融合 ：autonomous driving(title,abstract)；driving perception(abstract)；分类 cs.RO

Vision-RADAR fusion for Robotics BEV Detections: A Survey

Apoorv Singh

专题命中 多传感器融合 ：BEV(title,abstract)；LiDAR(abstract)；分类 cs.CV

Comments 6 pages, 6 figures, 2 tables

Romanus: Robust Task Offloading in Modular Multi-Sensor Autonomous Driving Systems

Luke Chen, Mohanad Odema, Mohammad Abdullah Al Faruque

专题命中 多传感器融合 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.CV

Comments This paper has been accepted to the 2022 International Conference On Computer-Aided Design (ICCAD 2022)

MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review

Zhiqing Wei, Fengkai Zhang, Shuo Chang, Yangyang Liu, Huici Wu, Zhiyong Feng

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.CV

Enabling Efficient Deep Convolutional Neural Network-based Sensor Fusion for Autonomous Driving

Xiaoming Zeng, Zhendong Wang, Yang Hu

专题命中 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；分类 cs.CV

The ApolloScape Open Dataset for Autonomous Driving and its Application

Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang

专题命中 多传感器融合 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.CV

Comments Version 4: Accepted by TPAMI. Version 3: 17 pages, 10 tables, 11 figures, added the application (DeLS-3D) based on the ApolloScape Dataset. Version 2: 7 pages, 6 figures, added comparison with BDD100K dataset

UnLoc: A Universal Localization Method for Autonomous Vehicles using LiDAR, Radar and/or Camera Input

Muhammad Ibrahim, Naveed Akhtar, Saeed Anwar, Ajmal Mian

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV、cs.AI

Comments UnLoc: A Universal Localization Method for Autonomous Vehicles using LiDAR, Radar and/or Camera Input has been accepted for publication in the Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)

Multi-Agent Deep Reinforcement Learning for Safe Autonomous Driving with RICS-Assisted MEC

Xueyao Zhang, Bo Yang, Xuelin Cao, Zhiwen Yu, George C. Alexandropoulos, Yan Zhang, Merouane Debbah, Chau Yuen

专题命中 多传感器融合 ：autonomous driving(title,abstract)；self-driving(abstract)

TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry Estimation

Leyuan Sun, Guanqun Ding, Yue Qiu, Yusuke Yoshiyasu, Fumio Kanehiro

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV、cs.AI

Comments Submitted to IEEE Sensors Journal with some modifications. This work has been submitted to the IEEE for possible publication

Journal ref JSEN.2023.3302401

t-READi: Transformer-Powered Robust and Efficient Multimodal Inference for Autonomous Driving

Pengfei Hu, Yuhang Qian, Tianyue Zheng, Ang Li, Zhe Chen, Yue Gao, Xiuzhen Cheng, Jun Luo

专题命中 多传感器融合 ：autonomous driving(title)；LiDAR(abstract)；分类 cs.RO、cs.CV、cs.AI

Comments 14 pages, 16 figures

Validation & Exploration of Multimodal Deep-Learning Camera-Lidar Calibration models

Venkat Karramreddy, Liam Mitchell

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV、cs.AI

Comments 8 pages, 10 figures

Autonomous Driving using Residual Sensor Fusion and Deep Reinforcement Learning

Amin Jalal Aghdasian, Amirhossein Heydarian Ardakani, Kianoush Aqabakee, Farzaneh Abdollahi

专题命中 多传感器融合 ：autonomous driving(title,abstract)；self-driving(abstract)

Comments Accepted Paper on International Conference on Robotics and Mechatronics (ICROM, 2023)

Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer

Hao Shao, Letian Wang, RuoBing Chen, Hongsheng Li, Yu Liu

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV、cs.AI

Comments Accepted at CoRL 2022

SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV、cs.AI

Comments Accepted to CoRL-2022

Ultra-Fusion: A Resilient Tightly-Coupled Multi-Sensor Fusion SLAM Framework under Sensor Degradation and Spatiotemporal Perturbation for Intelligent Transportation Systems

Ultra-Fusion：面向传感器退化与时空扰动下智能交通系统的鲁棒紧耦合多传感器融合SLAM框架

Yihong Tian, Junjie Zhang, Liuyang Li, Deteng Zhang, Yunfei Zuo, Jie Yin

机构 * Beijing Institute of Technology（北京理工大学） ； Chongqing University（重庆大学） ； Sichuan University（四川大学） ； Northwestern Polytechnical University（西北工业大学） ； Shanghai Jiao Tong University（上海交通大学） 纠错

专题命中 多传感器融合 ：LiDAR(summary_cn,abstract)；分类 cs.RO

AI总结 提出Ultra-Fusion紧耦合多传感器融合SLAM框架，通过可观测性感知初始化、因子级可靠性调度和在线LiDAR-IMU时空标定，在传感器退化与时空扰动下实现鲁棒定位，在多种平台和基准上验证了高精度与可用性。

Comments 19 pages

Effective Multi-sensor Conditioning for Street-view Novel-view Synthesis

面向街景新视角合成的有效多传感器条件控制

Zhengfei Kuang, Adam Sun, Liyuan Zhu, Tong Wu, Shengqu Cai, Jonathan Tremblay, Iro Armeni, Ehsan Adeli, Lior Yariv, Gordon Wetzstein

机构 * Stanford Univerity（斯坦福大学） ； NVIDIA 纠错

专题命中 多传感器融合 ：LiDAR(summary_cn,abstract)；分类 cs.CV

AI总结 提出StreetNVS视频扩散框架，通过参考增强相机注意力模块和相对射线级位置编码联合利用LiDAR、环视图像和相机位姿，实现稀疏LiDAR条件下的高质量街景新视角合成。

Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perception

Philipp Wolters, Johannes Gilg, Torben Teepe, Fabian Herzog, Anouar Laouichi, Martin Hofmann, Gerhard Rigoll

专题命中 多传感器融合 ：autonomous driving(abstract)；BEV(abstract)；LiDAR(abstract)；occupancy(abstract)

Comments Accepted to ICRA 2025

Native-Domain Cross-Attention for Camera-LiDAR Extrinsic Calibration Under Large Initial Perturbations

本域交叉注意机制用于大初始扰动下的相机-激光雷达外校准

Ni Ou, Zhuo Chen, Xinru Zhang, Junzheng Wang

机构 * School of Automation, Beijing Institute of Technology（北京理工大学自动化学院） ； School of Integrated Circuits and Electronics, Beijing Institute of Technology（北京理工大学集成电路与电子学院） 纠错

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

AI总结 本文提出一种本域交叉注意机制，通过直接对齐图像块和激光雷达点云实现可靠的跨模态交互，提升在大初始扰动下的外校准精度和鲁棒性。

Comments 8 pages, 3 figures