自动驾驶 - arXivDaily 专题

2210.11750 2022-10-24 cs.CV cs.RO eess.IV 82%

Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data

Kazuto Nakashima, Yumi Iwashita, Ryo Kurazume

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

Comments Accepted to WACV 2023

2203.01816 2022-09-07 cs.RO cs.CV eess.IV 82%

Intensity Image-based LiDAR Fiducial Marker System

Yibo Liu, Hunter Schofield, Jinjun Shan

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

Comments 8 pages

2203.05698 2022-08-02 cs.RO cs.AI cs.CV cs.LG 82%

Learning-based Localizability Estimation for Robust LiDAR Localization

Julian Nubert, Etienne Walther, Shehryar Khattak, Marco Hutter

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

Comments 8 pages, 7 figures, 4 tables

2109.08263 2021-11-18 eess.IV cs.CV cs.RO 82%

Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation

Simon Chamorro, Jack Collier, François Grondin

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

Journal ref 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

2111.01246 2021-11-03 eess.SP 82%

Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving

Ruxin Zheng, Shunqiao Sun, David Scharff, Teresa Wu

专题命中激光雷达：autonomous driving(title,abstract)；LiDAR(abstract)

Comments 6 pages, 9 figures

2102.11952 2021-08-03 cs.CV cs.RO eess.IV 82%

Learning to Drop Points for LiDAR Scan Synthesis

Kazuto Nakashima, Ryo Kurazume

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

Comments Accepted to IROS 2021

2106.11516 2021-07-02 cs.RO cs.AI cs.CV 82%

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

Lin Li, Xin Kong, Xiangrui Zhao, Wanlong Li, Feng Wen, Hongbo Zhang, Yong Liu

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

Comments 8 pages. Accepted by ICRA-2021

2105.12774 2021-05-28 cs.CV cs.AI cs.LG cs.RO 82%

DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained Autoencoder

Prashant Kumar, Sabyasachi Sahoo, Vanshil Shah, Vineetha Kondameedi, Abhinav Jain, Akshaj Verma, Chiranjib Bhattacharyya, Vinay Viswanathan

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

Comments 17 pages, 15 figures, Accepted at AAAI 2021

2103.15967 2021-03-31 cs.RO cs.CV eess.IV 82%

Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar

Brian H. Wang, Carlos Diaz-Ruiz, Jacopo Banfi, Mark Campbell

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

Comments Accepted to the 2021 IEEE International Conference on Robotics and Automation (ICRA)

2012.05740 2020-12-11 cs.CV cs.AI cs.RO 82%

R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection

Ruddy Théodose, Dieumet Denis, Thierry Chateau, Vincent Frémont, Paul Checchin

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

2003.04260 2020-03-26 cs.CV cs.RO eess.IV 82%

SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera

Weimin Wang, Shohei Nobuhara, Ryosuke Nakamura, Ken Sakurada

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

2003.01979 2020-03-05 cs.IT eess.SP math.IT 82%

Factory Automation: Resource Allocation of an Elevated LiDAR System with URLLC Requirements

Nalin Jayaweera, Dileepa Marasinghe, Nandana Rajatheva, Matti Latva-aho

专题命中激光雷达：LiDAR(title,abstract)；autonomous driving(abstract)

Comments Accepted in 6G Wireless Summit 2020

1908.07488 2020-01-14 eess.SP 82%

LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Aldebaro Klautau, Nuria González-Prelcic, Robert W. Heath

专题命中激光雷达：LiDAR(title,abstract)；autonomous driving(abstract)

Comments 10 pages, IEEE; update: fixed typo

1909.06700 2019-09-17 cs.RO cs.CV eess.IV 82%

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

Jiarong Lin, Fu Zhang

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

1907.07160 2019-07-17 cs.CV cs.RO eess.IV 82%

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

Yu Chen, Guan Wang

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

1807.00275 2018-07-04 cs.CV cs.AI cs.LG cs.RO 82%

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

Fangchang Ma, Guilherme Venturelli Cavalheiro, Sertac Karaman

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

Comments Software: https://github.com/fangchangma/self-supervised-depth-completion . Video: https://youtu.be/bGXfvF261pc . 12 pages, 6 figures, 3 tables

2602.10492 2026-02-12 cs.CV cs.RO 82%

End-to-End LiDAR optimization for 3D point cloud registration

端到端激光雷达优化用于3D点云配准

Siddhant Katyan, Marc-André Gardner, Jean-François Lalonde

机构 * Université Laval（拉瓦尔大学）； Bentley Systems（贝恩特系统）

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

AI总结本文提出端到端自适应激光雷达框架，通过动态调整参数优化点云配准，提升精度与效率，并在CARLA模拟中验证其优于固定参数方法的性能。

Comments 36th British Machine Vision Conference 2025, {BMVC} 2025, Sheffield, UK, November 24-27, 2025. Project page: https://lvsn.github.io/e2e-lidar-registration/

2412.15199 2024-12-20 cs.CV cs.LG cs.RO 82%

LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulation

Chenxu Zhou, Lvchang Fu, Sida Peng, Yunzhi Yan, Zhanhua Zhang, Yong Chen, Jiazhi Xia, Xiaowei Zhou

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

Comments Project page: https://zju3dv.github.io/lidar-rt

2302.07025 2023-11-09 cs.CV cs.LG eess.IV 82%

Optimal Transport for Change Detection on LiDAR Point Clouds

Marco Fiorucci, Peter Naylor, Makoto Yamada

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

Comments This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No101027956. Marie Skłodowska-Curie Action (Individual Fellowship): OPtimal Transport for Identifying Marauder Activities on LiDAR (OPTIMAL) https://cordis.europa.eu/project/id/101027956

Journal ref IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 982-985

2301.09257 2023-06-21 cs.CV cs.RO 82%

Real-Time Simultaneous Localization and Mapping with LiDAR intensity

Wenqiang Du, Giovanni Beltrame

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

Comments Accepted by ICRA 2023, code released: https://github.com/SnowCarter/Intensity_based_LiDAR_SLAM.git

2210.14612 2023-05-16 cs.CV cs.LG cs.NE cs.RO 82%

Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception

Marc Uecker, Tobias Fleck, Marcel Pflugfelder, J. Marius Zöllner

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

Comments Accepted at the NeurIPS 2022 Workshop on Machine Learning for Autonomous Driving (ML4AD). Changed in v3: corrected erroneously cited mIoU score for PolarNet

2007.13834 2021-11-10 cs.CV cs.LG eess.IV 82%

Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

Eyal Gofer, Shachar Praisler, Guy Gilboa

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

Comments Accepted for publication in IEEE Transactions on Image Processing. For associated examples, see https://www.vision-and-sensing.com/post/adaptive-lidar-sampling-and-depth-completion-using-ensemble-variance-new-publication

2102.04960 2021-06-21 cs.CV cs.RO 82%

Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

Huan Yin, Xuecheng Xu, Yue Wang, Rong Xiong

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

Comments Published by Frontiers in Robotics and AI. The published version is available at https://www.frontiersin.org/articles/10.3389/frobt.2021.661199/full . The source code is available at https://github.com/ZJUYH/radar-to-lidar-place-recognition

2105.01793 2021-05-06 cs.CV eess.IV 82%

Intensity Harmonization for Airborne LiDAR

David Jones, Nathan Jacobs

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

Comments IGARSS 2021. Project website with video and code at https://davidthomasjones.me/publications/airborne-lidar-intensity-harmonization

1911.10575 2019-12-03 eess.IV cs.CV cs.LG 82%

Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation

Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Mohamed Shawky

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

Comments Accepted in Machine learning for Autonomous Driving NeurIPS 2019 Workshop

1902.10226 2019-02-28 eess.IV cs.CV cs.LG stat.ML 82%

TensorMap: Lidar-Based Topological Mapping and Localization via Tensor Decompositions

Sirisha Rambhatla, Nikos D. Sidiropoulos, Jarvis Haupt

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

Comments 5 pages; Index Terms - Topological maps, Lidar, Localization of Autonomous Vehicles, Orthogonal Tucker Decomposition, and Scan-matching

Journal ref 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

2606.05506 2026-08-07 cs.CV 版本更新 81%

Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning

基于特权传感器引导对比学习的点目标导航鲁棒场景迁移

Amirhossein Zhalehmehrabi, Tiziano Tezze, Alberto Castelini, Alessandro Farinelli

机构 * University of Padua（帕多瓦大学）； ETH Zurich（苏黎世联邦理工学院）

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

AI总结提出一种传感器引导的自适应对比学习框架，利用特权LiDAR传感器在训练时引导视觉编码器学习导航相关结构，并通过解耦表征学习与策略优化以及跨阶段域不匹配来提升策略级场景迁移能力。

Comments 8 pages, Accepted to IEEE Robotics and Automation Letters (RA-L)

2506.14243 2026-08-07 cs.CV 版本更新 81%

Multi-Representation Geometric Hierarchy Fusion: An Implicit-Submap Driven Framework for Resilient 3D Place Recognition

多表示几何层次融合：一种用于鲁棒三维地点识别的隐式子图驱动框架

Xiaohui Jiang, Haijiang Zhu, Chade Li, Ning An

机构 * College of Information and Technology, Beijing University of Chemical Technology（信息与技术学院，北京化工大学）； School of Artificial Intelligence, University of Chinese Academy of Sciences（人工智能学院，中国科学院大学）； Research Institute of Mine Artificial Intelligence, China Coal Research Institute（矿山人工智能研究院，中国煤炭科研院）

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

AI总结针对激光雷达地点识别中描述子不稳定与表示脆弱性问题，本文提出隐式神经点驱动的多表示几何层次融合框架，在多数据集上实现鲁棒性能，平衡了精度、效率与内存占用。

2607.15036 2026-07-17 cs.RO 新提交 81%

Learning Agile Navigation in Crowded Environments for Quadruped Robots

学习四足机器人在拥挤环境中的敏捷导航

Shuyu Wu, Zeyu Liu, Tianbao Zhang, Fanxing Li, Fangyu Sun, Mingkang Xiong, Wei Xi, Wenxian Yu, Danping Zou

机构 * Shanghai Jiao Tong University（上海交通大学）； Midea Group（美的集团）

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

AI总结针对四足机器人在拥挤环境中导航难题，提出结合VO几何安全与端到端学习敏捷性的VOP-Nav系统，利用LiDAR数据隐式编码约束并预测安全速度区，VO预测兼具推理输入与训练奖励双重作用，实验验证其高效性与稳健性。

2607.01079 2026-07-02 cs.RO 新提交 81%

Where Am I? Semantic Map Grounding via Vision-Language Models for Multi-Modal Localization

我在哪里？基于视觉-语言模型的语义地图定位用于多模态定位

Suraj Borate, Aarav Shah, Madhu Vadali

机构 * IIT Gandhinagar（印度理工学院甘地讷格尔分校）

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

AI总结将机器人定位重构为语义推理任务，使用微调的Qwen2.5-VL-7B模型融合摄像头、LiDAR和语义地图预测位姿，在室内数据集上达到98.23%位置精度，并展现出跨模态互补性和对新场景的泛化能力。

1. 激光雷达 3131 篇

Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data

Intensity Image-based LiDAR Fiducial Marker System

Learning-based Localizability Estimation for Robust LiDAR Localization

Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation

Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving

Learning to Drop Points for LiDAR Scan Synthesis

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained Autoencoder

Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar

R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection

SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera

Factory Automation: Resource Allocation of an Elevated LiDAR System with URLLC Requirements

LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

End-to-End LiDAR optimization for 3D point cloud registration

LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulation

Optimal Transport for Change Detection on LiDAR Point Clouds

Real-Time Simultaneous Localization and Mapping with LiDAR intensity

Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception

Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

Intensity Harmonization for Airborne LiDAR

Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation

TensorMap: Lidar-Based Topological Mapping and Localization via Tensor Decompositions

Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning

Multi-Representation Geometric Hierarchy Fusion: An Implicit-Submap Driven Framework for Resilient 3D Place Recognition

Learning Agile Navigation in Crowded Environments for Quadruped Robots

Where Am I? Semantic Map Grounding via Vision-Language Models for Multi-Modal Localization