多模态信息融合 - arXivDaily 专题

2109.07982 2021-09-17 cs.RO cs.CV 62%

R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

Jiarong Lin, Fu Zhang

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Submitted to IEEE Robotics and Automation Letters

1908.03918 2021-09-14 cs.LG cs.CV cs.RO stat.ML 62%

DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction

Changhao Chen, Chris Xiaoxuan Lu, Bing Wang, Niki Trigoni, Andrew Markham

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

2108.05013 2021-08-21 cs.RO cs.CV 62%

Elastic Tactile Simulation Towards Tactile-Visual Perception

Yikai Wang, Wenbing Huang, Bin Fang, Fuchun Sun, Chang Li

专题命中机器人多传感器融合：information fusion(abstract)；分类 cs.CV、cs.RO

Comments ACMMM 2021 (Oral). Code available at https://github.com/yikaiw/EIP. arXiv admin note: substantial text overlap with arXiv:2011.11528

2108.01246 2021-08-04 cs.RO cs.CV 62%

AcousticFusion: Fusing Sound Source Localization to Visual SLAM in Dynamic Environments

Tianwei Zhang, Huayan Zhang, Xiaofei Li, Junfeng Chen, Tin Lun Lam, Sethu Vijayakumar

专题命中机器人多传感器融合：audio-visual fusion(abstract)；分类 cs.CV、cs.RO

Comments Accepted by IROS-2021

2107.04013 2021-07-09 cs.CV cs.AI cs.LG cs.RO 62%

Multi-Modality Task Cascade for 3D Object Detection

Jinhyung Park, Xinshuo Weng, Yunze Man, Kris Kitani

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

2105.08837 2021-05-20 cs.RO cs.CV 62%

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments

Sachini Herath, Saghar Irandoust, Bowen Chen, Yiming Qian, Pyojin Kim, Yasutaka Furukawa

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments To be published in ICRA 2021. Code and data: https://github.com/Sachini/Fusion-DHL

Journal ref ICRA 2021

2010.09076 2021-04-06 cs.CV cs.RO 62%

RADIATE: A Radar Dataset for Automotive Perception in Bad Weather

Marcel Sheeny, Emanuele De Pellegrin, Saptarshi Mukherjee, Alireza Ahrabian, Sen Wang, Andrew Wallace

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

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

2103.14965 2021-03-30 cs.RO cs.LG cs.SY eess.SP eess.SY 62%

Transmitter Discovery through Radio-Visual Probabilistic Active Sensing

Luca Varotto, Angelo Cenedese

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 eess.SP、cs.RO

Comments 7 pages, 4 figures, 1 table, submitted to MMAR 2021

2103.14286 2021-03-29 cs.RO cs.CV 62%

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

Ming Zhang, Mingming Zhang, Yiming Chen, Mingyang Li

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021

2010.13750 2020-10-27 cs.CV cs.LG cs.RO 62%

Demo Abstract: Indoor Positioning System in Visually-Degraded Environments with Millimetre-Wave Radar and Inertial Sensors

Zhuangzhuang Dai, Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu, Niki Trigoni, Andrew Markham

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Appear as demo abstract at the ACM Conference on Embedded Networked Sensor Systems (SenSys 2020)

2009.06292 2020-09-15 cs.RO cs.CV cs.LG 62%

A Multisensory Learning Architecture for Rotation-invariant Object Recognition

Murat Kirtay, Guido Schillaci, Verena V. Hafner

专题命中机器人多传感器融合：multimodal fusion(abstract)；分类 cs.CV、cs.RO

Comments The manuscript consists of 8 pages with 6 figures and two results tables. Additionally, we provide a dedicated website to reach the dataset that we employed for this study: http://www.robotmultimodal.com/datasets/

1910.03126 2020-07-30 cs.RO cs.CV 62%

Improvements to Target-Based 3D LiDAR to Camera Calibration

Jiunn-Kai Huang, Jessy W. Grizzle

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Journal ref IEEE Access, vol. 8, 2020, pp. 134101-134110

1911.09968 2020-07-24 cs.CV cs.LG eess.IV 62%

SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation

Yasin Almalioglu, Mehmet Turan, Alp Eren Sari, Muhamad Risqi U. Saputra, Pedro P. B. de Gusmão, Andrew Markham, Niki Trigoni

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、eess.IV

Comments 15 pages, submitted to The IEEE Transactions on Robotics (T-RO) journal, under review

2005.00709 2020-05-05 cs.RO eess.SP 62%

TEX-CUP: The University of Texas Challenge for Urban Positioning

Lakshay Narula, Daniel M. LaChapelle, Matthew J. Murrian, J. Michael Wooten, Todd E. Humphreys, Elliot de Toldi, Guirec Morvant, Jean-Baptiste Lacambre

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 eess.SP、cs.RO

Comments 8 pages, 6 figures. To appear in IEEE/ION Position, Location, and Navigation Symposium (PLANS), 2020

1912.04527 2020-04-15 cs.LG cs.CV cs.RO stat.ML 62%

Learning Pose Estimation for UAV Autonomous Navigation andLanding Using Visual-Inertial Sensor Data

Francesca Baldini, Animashree Anandkumar, Richard M. Murray

专题命中机器人多传感器融合：multimodal fusion(abstract)；分类 cs.CV、cs.RO

1904.13279 2020-03-20 cs.RO eess.SP 62%

Incrementally Learned Mixture Models for GNSS Localization

Tim Pfeifer, Peter Protzel

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 eess.SP、cs.RO

Comments 8 pages, 5 figures, published in proceedings of IEEE Intelligent Vehicles Symposium (IV) 2019

2003.07240 2020-03-17 cs.RO eess.SP 62%

WiFi-Inertial Indoor Pose Estimation for Micro Aerial Vehicles

Shengkai Zhang, Wei Wang, Tao Jiang

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 eess.SP、cs.RO

Comments To appear in IEEE Transactions on Industrial Electronics

1910.02106 2019-10-08 cs.RO cs.CV 62%

Direct Visual-Inertial Odometry with Semi-Dense Mapping

Wenju Xu, Dongkyu Choi, Guanghui Wang

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

1904.06993 2019-08-30 cs.RO cs.CV 62%

Tightly Coupled 3D Lidar Inertial Odometry and Mapping

Haoyang Ye, Yuying Chen, Ming Liu

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Accepted by ICRA 2019

1903.08960 2019-07-30 cs.CV cs.AI cs.LG cs.RO 62%

Short-Term Prediction and Multi-Camera Fusion on Semantic Grids

Lukas Hoyer, Patrick Kesper, Anna Khoreva, Volker Fischer

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

1706.02908 2019-03-14 cs.RO cs.CV 62%

Multi-Modal Obstacle Detection in Unstructured Environments with Conditional Random Fields

Mikkel Kragh, James Underwood

专题命中机器人多传感器融合：multimodal fusion(abstract)；分类 cs.CV、cs.RO

Comments This is the accepted version of the following article: Kragh M, Underwood J. Multimodal obstacle detection in unstructured environments with conditional random fields. J Field Robotics. 2019, 1-20., which has been published in final form at https://doi.org/10.1002/rob.21866

1901.11284 2019-02-01 cs.RO cs.CV 62%

Capturing Object Detection Uncertainty in Multi-Layer Grid Maps

Sascha Wirges, Marcel Reith-Braun, Martin Lauer, Christoph Stiller

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments 8 pages, 8 figures, 2 tables

1802.08515 2018-02-26 cs.RO cs.CV 62%

Closed-form solution to cooperative visual-inertial structure from motion

Agostino Martinelli

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

1705.10279 2017-05-30 cs.RO cs.AI cs.CV 62%

Towards Visual Ego-motion Learning in Robots

Sudeep Pillai, John J. Leonard

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Conference paper; Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017, Vancouver CA; 8 pages, 8 figures, 2 tables

1702.03435 2017-02-14 cs.RO cs.CV 62%

Distributed Mapping with Privacy and Communication Constraints: Lightweight Algorithms and Object-based Models

Siddharth Choudhary, Luca Carlone, Carlos Nieto, John Rogers, Henrik I. Christensen, Frank Dellaert

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments preprint for IJRR submission

1604.04528 2016-04-18 cs.CV cs.LG cs.NE cs.RO 62%

Tracking Human-like Natural Motion Using Deep Recurrent Neural Networks

Youngbin Park, Sungphill Moon, Il Hong Suh

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments submitted to ECCV 2016

1703.00154 2018-06-11 cs.CV stat.AP 61%

Inertial Odometry on Handheld Smartphones

Arno Solin, Santiago Cortes, Esa Rahtu, Juho Kannala

专题命中机器人多传感器融合：information fusion(abstract,comments)；分类 cs.CV

Comments Appearing in Proceedings of the International Conference on Information Fusion (FUSION 2018)

2605.11048 2026-08-26 cs.RO cs.AI 版本更新 57%

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

ForceFlow: 通过接触驱动的流匹配学习感知与行动

Shuoheng Zhang, Yifu Yuan, Hongyao Tang, Yan Zheng, Qiaojun Yu, Pengyi Li, Guowei Huang, Helong Huang, Xingyue Quan, Jianye Hao

机构 * Tianjin University（天津大学）； Huawei Noah's Ark Lab（华为诺亚实验室）； Shanghai AI Lab（上海人工智能实验室）

专题命中机器人多传感器融合：multimodal fusion(abstract)；分类 cs.RO

AI总结本文提出ForceFlow框架，通过融合力信号与多模态信息，提升机器人在复杂接触任务中的鲁棒性和泛化能力，实验显示其在六个真实任务中成功率提升37%。

2608.21699 2026-08-25 cs.RO 新提交 57%

Towards insect-like distributed proprioception in actuators and appendages for flapping-wing insect-scale aerial robots

面向扑翼昆虫级空中机器人的作动器与附肢中类昆虫分布式本体感知

Alexander Hedrick, Arvind Gupta, Kaushik Jayaram

机构 * University of Colorado Boulder（科罗拉多大学博尔德分校）； Imperial College London（帝国理工学院）

专题命中机器人多传感器融合：sensor fusion(abstract)；分类 cs.RO

AI总结该研究针对扑翼昆虫级空中机器人，开发了两种嵌入式本体感知传感器，可精准跟踪冲程与俯仰角，实现碰撞检测与异步扑翼，有望提升机器人性能。

Comments 8 pages, 6 figures, this work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

2608.21355 2026-08-24 cs.RO 新提交 57%

ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations

ViTacPhys：基于人类视觉-触觉演示的感知物体物理属性的抓取方法

Yiwen Liu, Yujun Zhu, Kui Jia, Zhao Liao, Yangwei You, Shuaijun Wang

机构 * Xiaomi Robotics（小米机器人）

专题命中机器人多传感器融合：multimodal fusion(abstract)；分类 cs.RO

AI总结该研究提出ViTacPhys视觉-触觉框架，可从人类演示中估计物体物理属性，迁移至机器人后实现高抓取成功率，力曲线更贴合人类遥操作。

Comments 11 pages, 7 figures. Project page: https://vitacphys.github.io/ViTacPhys/

1. 机器人多传感器融合 931 篇

R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction

Elastic Tactile Simulation Towards Tactile-Visual Perception

AcousticFusion: Fusing Sound Source Localization to Visual SLAM in Dynamic Environments

Multi-Modality Task Cascade for 3D Object Detection

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments

RADIATE: A Radar Dataset for Automotive Perception in Bad Weather

Transmitter Discovery through Radio-Visual Probabilistic Active Sensing

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

Demo Abstract: Indoor Positioning System in Visually-Degraded Environments with Millimetre-Wave Radar and Inertial Sensors

A Multisensory Learning Architecture for Rotation-invariant Object Recognition

Improvements to Target-Based 3D LiDAR to Camera Calibration

SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation

TEX-CUP: The University of Texas Challenge for Urban Positioning

Learning Pose Estimation for UAV Autonomous Navigation andLanding Using Visual-Inertial Sensor Data

Incrementally Learned Mixture Models for GNSS Localization

WiFi-Inertial Indoor Pose Estimation for Micro Aerial Vehicles

Direct Visual-Inertial Odometry with Semi-Dense Mapping

Tightly Coupled 3D Lidar Inertial Odometry and Mapping

Short-Term Prediction and Multi-Camera Fusion on Semantic Grids

Multi-Modal Obstacle Detection in Unstructured Environments with Conditional Random Fields

Capturing Object Detection Uncertainty in Multi-Layer Grid Maps

Closed-form solution to cooperative visual-inertial structure from motion

Towards Visual Ego-motion Learning in Robots

Distributed Mapping with Privacy and Communication Constraints: Lightweight Algorithms and Object-based Models

Tracking Human-like Natural Motion Using Deep Recurrent Neural Networks

Inertial Odometry on Handheld Smartphones

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

Towards insect-like distributed proprioception in actuators and appendages for flapping-wing insect-scale aerial robots

ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations