自动驾驶

Cloud boundary height measurements using lidar and radar

Victor Venema, Herman Russchenberg, Arnoud Apituley, Andre van Lammeren, Leo Ligthart

专题命中 激光雷达 ：LiDAR(title,abstract)

Comments Reviewed conference contribution

Journal ref Physics and Chemistry of the Earth, 24, no. 2, pp. 129-134, 2000

Pierre Auger Atmosphere-Monitoring Lidar System

A. Filipcic, M. Horvat, D. Veberic, D. Zavrtanik, M. Zavrtanik, M. Chiosso, R. Mussa, G. Sequeiros, M. A. Mostafa, M. D. Roberts

专题命中 激光雷达 ：LiDAR(title,abstract)

Comments 4 pages, 6 figures, ICRC 2003 conference proceeding

CloudDiffusion: Diffusion-Based Scene Completion in the Point Cloud Domain

PointDiffusion: 点云领域的基于扩散的场景补全

Chidera Agbasiere, Mikhail Sannikov, Faith Ogunwoye, Erik Shaikhiev, Alex Kozinov, Ilya Mikhalchuk, Iana Zhura, Dzmitry Tsetserukou

机构 * Intelligent Space Robotics Laboratory, Skolkovo Institute of Science and Technology（斯科尔科沃科学技术学院智能空间机器人实验室） 纠错

专题命中 激光雷达 ：LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；分类 cs.CV

AI总结 提出多令牌高斯VAE和锚点ICP地面真值精化，实现单步扩散场景补全，在SemanticKITTI上平方倒角距离降低16倍，推理延迟降低25-143倍。

PathCover: A Fast Convex Decomposition along a Path via Randomized Iterative Space Partitioning (RISP) on Point Clouds

PathCover：基于点云的随机迭代空间划分（RISP）沿路径的快速凸分解

Kunal S. Narkhede, Abhijeet M. Kulkarni, Guoquan Huang, Ioannis Poulakakis

机构 * University of Delaware（特拉华大学） ； Athena Research Center（雅典娜研究中心） ； National Technical University of Athens（雅典国家技术大学） ； HERON–Center of Excellence in Robotics（赫伦机器人卓越中心） 纠错

专题命中 激光雷达 ：LiDAR(abstract,abstract_cn)；trajectory planning(abstract)；分类 cs.RO

AI总结 PathCover是基于点云的快速凸分解框架，采用RISP算法，可高效生成无障碍物多面体，速度较现有方法提升一个数量级，经仿真与实机验证适用于机器人导航。

Comments 13 pages, 5 figures

LiAuto-GeoX: Efficient Grounded Driving Transformer

LiAuto-GeoX: 高效接地驾驶Transformer

Jiawei Lian, Haoyi Sun, Yang Wu, Lifu Mu, Siyuan Wang, Le Hui, Ning Mao, Tao Wei, Pan Zhou, Kun Zhan, Jian Yang

机构 * Nanjing University of Science and Technology（南京理工大学） ； Li Auto Inc.（Li Auto公司） ； Northwestern Polytechnical University（西北工业大学） ； Department of Computing, The Hong Kong Polytechnic University（香港理工大学计算学院） 纠错

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.CV

AI总结 提出LiAuto-GeoX，通过稀疏激光雷达先验和几何保持蒸馏框架，实现高效、实时的自车中心密集3D重建，并显著提升下游自动驾驶任务性能。

KinematicRL: A Sim-to-Real Reinforcement Learning Framework For Social Navigation With Kinodynamic Feasibility

KinematicRL: 一种面向社交导航的具有运动学可行性的仿真到现实强化学习框架

Zhiming Xu, Haodong Yang, Chengju Liu, Qijun Chen, Chenpeng Yao

机构 * School of Computer Science and Technology, Tongji University（同济大学计算机科学与技术学院） ； Department of Electronics and Information Engineering, Tongji University（同济大学电子与信息工程学院） ； Shanghai Institute of Intelligent Science and Technology, Tongji University（同济大学上海智能科学与技术研究院） 纠错

专题命中 激光雷达 ：LiDAR(summary_cn,abstract)；分类 cs.RO

AI总结 提出KinematicRL框架，通过二阶控制动作空间、基于2D LiDAR的聚类人体追踪和无偏残差门控模块，解决社交导航中仿真到现实的动态可行性问题。

Comments Accepted by IEEE Transactions on Automation Science and Engineering (T-ASE)

Recent Advances and Trends in Learning-based 3D Representations

基于学习的3D表示的最新进展与趋势

Adrien Schockaert, Hamid Laga, Hazem Wannous, Vincent Magnier, Guillaume Dufaye, Jean-françois Witz

机构 * CERI SN, IMT Nord Europe（CERI SN，IMT Nord Europe） ； Univ. Lille, CNRS, Centrale Lille, UMR 9013 - LaMcube - Laboratoire de Mécanique, Multiphysique, Multiéchelle（里尔大学，CNRS，Centrale Lille，UMR 9013 - LaMcube - 机械、多物理场、多尺度实验室） ； Downs, 59670 Sainte-Marie-Cappel（Downs，59670 Sainte-Marie-Cappel） ； School of Information Technology, Murdoch University（墨尔本大学信息科技学院） 纠错

专题命中 激光雷达 ：LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；分类 cs.CV

AI总结 本文综述了从离散显式格式到连续隐式场（基于神经渲染或基元溅射）的3D表示家族，分析了其优缺点及关键应用，并强调了向隐式表示的范式转变。

SB-BEVFusion: Enhancing the Robustness against Sensor Malfunction and Corruptions

SB-BEVFusion：增强对传感器故障和损坏的鲁棒性

Markus Essl, Marta Moscati, Mubashir Noman, Muhammad Zaigham Zaheer, Usman Naseem, Shah Nawaz, Markus Schedl

机构 * Johannes Kepler University Linz（约翰·凯撒大学林茨分校） ； MBZUAI（穆罕默德·本·拉希德人工智能研究所） ； Macquarie University（麦考瑞大学） ； Linz Institute of Technology（林茨技术学院） 纠错

专题命中 激光雷达 ：BEV(abstract,abstract_cn)；LiDAR(abstract)；分类 cs.CV

AI总结 本文提出SB-BEVFusion框架，通过处理缺失或损坏的相机和激光雷达数据，提升自动驾驶3D目标检测在传感器故障和损坏场景下的鲁棒性。

Comments Accepted at ICIP 2026

Adaptive Dual-Weighted Gravitational Point Cloud Denoising Method

自适应双权重引力点云去噪方法

Ge Zhang, Chunyang Wang, Bin Liu, Guan Xi

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.CV

AI总结 本文提出一种自适应双权重引力点云去噪方法，通过八叉树空间划分、自适应体素统计和引力评分函数，提升去噪精度、边缘保持和实时性能。

Panoptic-CUDAL: Rural Australia Point Cloud Dataset in Rainy Conditions

Tzu-Yun Tseng, Alexey Nekrasov, Malcolm Burdorf, Bastian Leibe, Julie Stephany Berrio, Mao Shan, Zhenxing Ming, Stewart Worrall

机构 * The Australian Centre for Robotics (ACFR) at the University of Sydney（澳大利亚机器人中心（ACFR）于悉尼大学） ； RWTH Aachen University（亚琛RWTH大学） 纠错

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.CV

Diffusion-Based mmWave Radar Point Cloud Enhancement Driven by Range Images

Ruixin Wu, Zihan Li, Jin Wang, Xiangyu Xu, Zhi Zheng, Kaixiang Huang, Guodong Lu

机构 * The State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University（浙江大学机械工程学院流体动力与机械电子系统国家重点实验室） ； Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems, Zhejiang University（浙江大学工业大数据与机器人智能系统重点实验室） ； Robotics Research Center of Yuyao City, Ningbo（宁波余姚市机器人研究中心） ； State Key Laboratory of Robotics and Systems, Department of Mechatronics Engineering, Harbin Institute of Technology（哈尔滨工业大学机器人系统国家重点实验室） 纠错

专题命中 激光雷达 ：autonomous driving(abstract)；BEV(abstract)；LiDAR(abstract)；分类 cs.RO

Comments 8 pages, 7 figures. This work has been submitted to the IEEE for possible publication

PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection

Xia Chen, Jianren Wang, David Held, Martial Hebert

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；driving perception(abstract)；分类 cs.CV

Comments 3DV2020

Through the Perspective of LiDAR: A Feature-Enriched and Uncertainty-Aware Annotation Pipeline for Terrestrial Point Cloud Segmentation

通过LiDAR视角：一种特征丰富且不确定性感知的标注流程用于陆地点云分割

Fei Zhang, Rob Chancia, Josie Clapp, Amirhossein Hassanzadeh, Dimah Dera, Richard MacKenzie, Jan van Aardt

机构 * Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA（切斯特·F·卡尔森成像科学中心，罗切斯特理工学院，罗切斯特，纽约州，美国） 纠错

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

AI总结 本文提出一种半自动标注流程，通过球面投影和特征丰富技术提升陆地点云分割的效率与精度，构建了Mangrove3D数据集并验证了特征重要性，为生态监测提供高质量分割方案。

Comments 40 pages (28 main text), 20 figures, 4 supplementary materials; links to 3D point animations are included in the last table

Zero-shot detection of buildings in mobile LiDAR using Language Vision Model

June Moh Goo, Zichao Zeng, Jan Boehm

机构 * Department of Civil, Environmental and Geomatic Engineering, University College London（伦敦大学学院建筑、环境与地理工程系） 纠错

专题命中 激光雷达 ：LiDAR(title)；分类 cs.CV、cs.AI

Comments 7 pages, 6 figures, conference

Journal ref The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2024)

Comparing roughness maps generated by five roughness descriptors for LiDAR-derived digital elevation models

Lei Fan, Yang Zhao

专题命中 激光雷达 ：LiDAR(title)；分类 cs.CV、eess.IV

Comments 14 pages, 6 figures

DeepPointMap: Advancing LiDAR SLAM with Unified Neural Descriptors

Xiaze Zhang, Ziheng Ding, Qi Jing, Yuejie Zhang, Wenchao Ding, Rui Feng

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing

Kangcheng Liu

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments International Conference on Robotics and Automation (ICRA) 2022, 6 Figures. arXiv admin note: substantial text overlap with arXiv:2312.01262

Pose-Graph Attentional Graph Neural Network for Lidar Place Recognition

Milad Ramezani, Liang Wang, Joshua Knights, Zhibin Li, Pauline Pounds, Peyman Moghadam

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments 10 pages, 5 figures, 5 tables, Accepted for Publication in the IEEE Robotics and Automation Letters (RA-L)

HybridFusion: LiDAR and Vision Cross-Source Point Cloud Fusion

Yu Wang, Shuhui Bu, Lin Chen, Yifei Dong, Kun Li, Xuefeng Cao, Ke Li

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

P2Net: A Post-Processing Network for Refining Semantic Segmentation of LiDAR Point Cloud based on Consistency of Consecutive Frames

Yutaka Momma, Weimin Wang, Edgar Simo-Serra, Satoshi Iizuka, Ryosuke Nakamura, Hiroshi Ishikawa

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups

Jorge Beltrán, Carlos Guindel, Arturo de la Escalera, Fernando García

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments Published on IEEE Transactions on Intelligent Transportation Systems

Journal ref IEEE Transactions on Intelligent Transportation Systems, 2022

Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud

Xiaqing Ding, Xuecheng Xu, Sha Lu, Yanmei Jiao, Mengwen Tan, Rong Xiong, Huanjun Deng, Mingyang Li, Yue Wang

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments Paper accepted in the 2022 IEEE International Conference on Robotics and Automation (ICRA)

Robot Localization and Navigation through Predictive Processing using LiDAR

Daniel Burghardt, Pablo Lanillos

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.AI

Comments 2nd International Workshop on Active Inference IWAI2021, European Conference on Machine Learning (ECML/PCKDD 2021)

Person-MinkUNet: 3D Person Detection with LiDAR Point Cloud

Dan Jia, Bastian Leibe

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments accepted as an extended abstract in JRDB-ACT Workshop at CVPR21

FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling

Kangcheng Liu, Zhi Gao, Feng Lin, Ben M. Chen

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

3D Surface Reconstruction from Voxel-based Lidar Data

Luis Roldão, Raoul de Charette, Anne Verroust-Blondet

专题命中 激光雷达 ：LiDAR(title)；分类 cs.RO、cs.CV

Comments IEEE Intelligent Transportation Systems Conference (ITSC) 2019

WiWorld-RealData: A Real-World Multi-Modal Dataset for 6G Wireless World Models

WiWorld-RealData：用于6G无线世界模型的真实世界多模态数据集

Yinyin Jiao, Huixin Xu, Jianhua Zhang, Yuelong Qiu, Jingjing Wang, Shaoyi Liu, Yuxiang Zhang, Li Yu, Xuebin Sun, Guangyi Liu

专题命中 激光雷达 ：LiDAR(summary_cn,abstract_cn)

AI总结 提出WiWorld-RealData数据集，包含3.7 GHz和6.775 GHz的信道冲激响应、多视角图像、全景图像、LiDAR点云、毫米波雷达记录和GNSS轨迹，支持环境辅助的信道预测，路径损耗预测MAE为2.02 dB。

Comments 6 pages, 6 figures, 3 tables

Single-Frame Point-Pixel Registration via Supervised Cross-Modal Feature Matching

基于监督跨模态特征匹配的单帧点像素配准

Yu Han, Zhiwei Huang, Yanting Zhang, Fangjun Ding, Shen Cai, Xiaoyu Tang, Yanchao Dong, Rui Fan

机构 * School of Information and Intelligent Science, Donghua University（信息与智能科学学院，东华大学） 纠错

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV、cs.AI

AI总结 研究激光雷达点云和相机图像的点像素配准难题，提出基于投影的无检测器框架及重复性评分机制，通过实验证明该方法在单帧激光雷达下能达先进性能，优于现有方法。

IntentNet: Learning to Predict Intention from Raw Sensor Data

Sergio Casas, Wenjie Luo, Raquel Urtasun

专题命中 激光雷达 ：self-driving(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV、cs.AI

Comments CoRL 2018

A Quick Review on Recent Trends in 3D Point Cloud Data Compression Techniques and the Challenges of Direct Processing in 3D Compressed Domain

Mohammed Javed, MD Meraz, Pavan Chakraborty

专题命中 激光雷达 ：autonomous driving(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV、eess.IV