多模态信息融合

Intelligent real-time MEMS sensor fusion and calibration

Dusan Nemec, Ales Janota, Marian Hrubos, Vojtech Simak

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

Journal ref IEEE Sensors Journal, vol. 16, no. 19, pp. 7150-7160, Oct.1, 2016

Decentralized Sensor Fusion With Distributed Particle Filters

Matthew Rosencrantz, Geoffrey Gordon, Sebastian Thrun

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

Comments Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)

Adaptive Entropy-Driven Sensor Selection in a Camera-LiDAR Particle Filter for Single-Vessel Tracking

相机-激光雷达粒子滤波器中用于单船跟踪的自适应熵驱动传感器选择

Andrei Starodubov, Yaqub Aris Prabowo, Andreas Hadjipieris, Ioannis Kyriakides, Roberto Galeazzi

机构 * Cyprus Marine and Maritime Institute（塞浦路斯海洋与航海研究所） ； Technical University of Denmark（丹麦技术大学） 纠错

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

AI总结 研究单船跟踪问题，提出含相机-激光雷达融合的粒子滤波器及信息增益自适应传感策略，在实际海事部署中验证，该策略能依信息增益切换模态，实现精度与连续性平衡，提供实用基线。

Comments 10 pages, 5 figures, submitted and accepted FUSION 2026 conference proceedings

Looking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-Making

观察与聆听内外：多模态人工智能系统用于驾驶员安全评估和智能车辆决策

Ross Greer, Laura Fleig, Maitrayee Keskar, Erika Maquiling, Giovanni Tapia Lopez, Angel Martinez-Sanchez, Parthib Roy, Jake Rattigan, Mira Sur, Alejandra Vidrio, Thomas Marcotte, Mohan Trivedi

机构 * Machine Intelligence, Interaction, and Imagination (Mi3) Laboratory（机器智能、交互与想象实验室） ； Laboratory for Intelligent and Safe Automobiles (LISA)（智能与安全汽车实验室） ； Johns Hopkins University（约翰霍普金斯大学） ； Center for Medicinal Cannabis Research (CMCR)（医药大麻研究中心） 纠错

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

AI总结 本文提出L-LIO框架，通过融合音频与视觉数据提升驾驶员状态评估和环境理解，探讨音频在车辆安全中的作用，包括驾驶员语音分类、乘客指令分析及视觉不足时的音频辅助。

A Novel ViDAR Device With Visual Inertial Encoder Odometry and Reinforcement Learning-Based Active SLAM Method

Zhanhua Xin, Zhihao Wang, Shenghao Zhang, Wanchao Chi, Yan Meng, Shihan Kong, Yan Xiong, Chong Zhang, Yuzhen Liu, Junzhi Yu

机构 * State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University（turbulence和复杂系统国家重点实验室，先进制造与机器人系，工程学院，北京大学） ； Tencent RoboticsX（腾讯机器人科技） ； College of Information and Electrical Engineering, China Agricultural University（信息与电气工程学院，中国农业大学） 纠错

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

Comments 12 pages, 13 figures

Journal ref IEEE Transactions on Industrial Informatics, pp. 1-12, 2025

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

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

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

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

GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multi-sensor Fused Odometry with Gaussian Mapping

Sheng Hong, Chunran Zheng, Yishu Shen, Changze Li, Fu Zhang, Tong Qin, Shaojie Shen

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

YOCO: You Only Calibrate Once for Accurate Extrinsic Parameter in LiDAR-Camera Systems

Tianle Zeng, Dengke He, Feifan Yan, Meixi He

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

Comments IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Journal ref IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT2024

Deep Learning for Inertial Positioning: A Survey

Changhao Chen, Xianfei Pan

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

Comments Accepted by IEEE Transactions on Intelligent Transportation Systems

DBA-Fusion: Tightly Integrating Deep Dense Visual Bundle Adjustment with Multiple Sensors for Large-Scale Localization and Mapping

Yuxuan Zhou, Xingxing Li, Shengyu Li, Xuanbin Wang, Shaoquan Feng, Yuxuan Tan

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

Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalities

Runwei Guan, Haocheng Zhao, Shanliang Yao, Ka Lok Man, Xiaohui Zhu, Limin Yu, Yong Yue, Jeremy Smith, Eng Gee Lim, Weiping Ding, Yutao Yue

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

Comments 18 pages, 9 figures

A Multi-modal Approach to Single-modal Visual Place Classification

Tomoya Iwasaki, Kanji Tanaka, Kenta Tsukahara

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

Comments 7 pages, 6 figures, 1 table

LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

Jiunn-Kai Huang, Shoutian Wang, Maani Ghaffari, Jessy W. Grizzle

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

Journal ref IEEE Robotics and Automation Letters, 31 March 2021

Hierarchical Multi-Process Fusion for Visual Place Recognition

Stephen Hausler, Michael Milford

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

Comments Pre-print version of article which will be presented at ICRA 2020

Real-time 3D Human Tracking for Mobile Robots with Multisensors

Mengmeng Wang, Daobilige Su, Lei Shi, Yong Liu, Jaime Valls Miro

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

Sensor fusion on MagAO-X: real time vibration control using accelerometers

MagAO-X上的传感器融合：利用加速度计实现实时振动控制

Parker T. Johnson, Jared R. Males, Povilas Palunas, Olivier Guyon, Sebastiaan Haffert, Joseph Long, Vincent Deo, Julien Lozi, Laird M. Close, Maggie Kautz, Jay Kueny, Jialin Li, Joshua Liberman, Miles Lucas, Matthijs Mars, Eden McEwen, Tiffany Nguyen, Elena Tonucci, Katie Twitchell

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 针对MagAO-X极端AO仪器，设计低成本模块化加速度计遥测系统，识别望远镜振动源并分析其与WFE的相关性，为AO系统预测控制提供基础。

Comments 13 pages, 9 figures, proceeding of SPIE Astronomical Telescopes + Instrumentation 2026 (Paper No. 14150-87)

Bounds on Multiple Sensor Fusion

多传感器融合的界限

Bill Moran, Fred Cohen, Zengfu Wang, Sofia Suvorova, Douglas Cochran, Tom Taylor, Peter Farrell, Stephen Howard

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 研究多传感器数据融合中因重叠导致的计数误差，通过线性规划分析传感器区域几何结构，定义融合多面体工具并推导正交条件，证明矩形扩展铺砖方案不满足而六边形扩展方案满足。

Comments 23 pages

Sensor Fusion for Track Geometry Monitoring: Integrating On-Board Condition Monitoring and Degradation Models via Kalman Filtering

轨道几何监测的传感器融合：通过卡尔曼滤波集成车载状态监测与退化模型

Huy Truong-Ba, Jacky Chin, Michael E. Cholette, Pietro Borghesani

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 本研究提出一种通过卡尔曼滤波融合低成本车载传感器振动信号与退化模型的方法，以提升轨道几何预测的可靠性，并实验验证了频繁传感器数据能显著降低预测不确定性。

A Robust 5G Terrestrial Positioning System with Sensor Fusion in GNSS-denied Scenarios

一种在GNSS受限场景下的鲁棒5G地面定位系统

Hamed Talebian, Nazrul Mohamed Nazeer, Darius Chmieliauskas, Jakub Nikonowicz, Mehdi Haghshenas, Łukasz Matuszewski, Mairo Leier, Aamir Mahmood

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 本文提出基于5G基础设施的地面定位系统，用于替代GNSS，在GNSS信号被阻挡或不可用时提供定位服务。通过多载波CP技术和深度学习模型实现鲁棒定位，适用于复杂环境。

Comments Submitted to IEEE Transactions on Vehicular Technology

Axle Sensor Fusion for Online Continual Wheel Fault Detection in Wayside Railway Monitoring

轴传感器融合用于在线持续轮故障检测在铁路旁侧监控

Afonso Lourenço, Francisca Osório, Diogo Risca, Goreti Marreiros

机构 * GECAD, ISEP, Polytechnic of Porto（GECAD、ISEP、波尔图理工大学） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 本文提出了一种基于轴传感器融合和持续学习的铁路轮故障检测方法，通过变分自编码器和梯度提升分类器实现在线持续检测，适应动态操作条件。

Adaptive Tuning of the Unscented Kalman Filter using Particle Swarm Optimization for Inertial-GPS Sensor Fusion Systems

基于粒子群优化的自适应无迹卡尔曼滤波器在惯性导航-GPS传感器融合系统中的应用

Psyche T. Malabo, Bobby D. Gerardo

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 本文提出基于粒子群优化的自适应UKF方法，通过优化参数提升IMU-GPS融合精度，实现82.14%的准确率提升和21606.59米的漂移减少。

Using LLMs for Late Multimodal Sensor Fusion for Activity Recognition

利用大语言模型进行晚阶段多模态传感器融合以进行活动识别

Ilker Demirel, Karan Thakkar, Benjamin Elizalde, Miquel Espi Marques, Aditya Sarathy, Yang Bai, Umamahesh Srinivas, Jiajie Xu, Shirley Ren, Jaya Narain

机构 * Apple（苹果公司） ； MIT（麻省理工学院） ； Johns Hopkins（约翰霍普金斯大学） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(title)

AI总结 利用大语言模型进行晚阶段多模态融合，实现零样本和单样本活动分类，无需特定任务训练。

Comments NeurIPS Workshop on Learning from Time Series for Health

OmniFuser: Adaptive Multimodal Fusion for Service-Oriented Predictive Maintenance

Ziqi Wang, Hailiang Zhao, Yuhao Yang, Daojiang Hu, Cheng Bao, Mingyi Liu, Kai Di, Schahram Dustdar, Zhongjie Wang, Shuiguang Deng

机构 * School of Software Technology, Zhejiang University（浙江大学软件学院） ； School of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院） ； Faculty of Computing, Harbin Institute of Technology（哈尔滨工业大学计算机学院） ； Hangzhou School of Automation, Zhejiang Normal University（浙江师范大学杭州自动化学院） ； Distributed Systems Group at the TU Wien and with ICREA at the UPF, Barcelona（维也纳大学分布式系统组和巴塞罗那大学ICREA） 纠错

专题命中 机器人多传感器融合 ：multimodal fusion(title)

A virtual sensor fusion approach for state of charge estimation of lithium-ion cells

Davide Previtali, Daniele Masti, Mirko Mazzoleni, Fabio Previdi

机构 * Department of Management, Information and Production Engineering（管理、信息与生产工程系） ； University of Bergamo（贝拉米奥大学） ； Gran Sasso Science Institute（格兰·萨索科学研究所） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(title)

Multi-Modal Sensor Fusion for Proactive Blockage Prediction in mmWave Vehicular Networks

Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim, Asmaa Abdallah, Daji Qiao, Ahmed M. Eltawil

机构 * Department of Electrical and Computer Engineering, Iowa State University of Science and Technology（电气与计算机工程系，爱荷华州立大学） ； Computer, Electrical, and Mathematical Sciences & Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST)（国王 Abdullah 科学与技术大学（KAUST）计算机、电气和数学科学与工程（CEMSE）系） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(title)

Comments Accepted in IEEE Asilomar Conference on Signals, Systems, and Computers 2025

Sensor Fusion Methods for Gaussian Mixture Models

Ishan Paranjape, Islam Hussein, Jeremy Murray-Krezan, Sean Phillips, Suman Chakravorty

专题命中 机器人多传感器融合 ：sensor fusion(title)

Comments 8 pages, to be modified and reduced in size for MFI 2025

Dual Unscented Kalman Filter Architecture for Sensor Fusion in Water Networks Leak Localization

Luis Romero-Ben, Paul Irofti, Florin Stoican, Vicenç Puig

专题命中 机器人多传感器融合 ：sensor fusion(title)

Dynamic Spectral fluorescence microscopy via Event-based & CMOS image-sensor fusion

Richard G. Baird, Apratim Majumder, Rajesh Menon

专题命中 机器人多传感器融合 ：sensor fusion(title)

Pose estimation of CubeSats via sensor fusion and Error-State Extended Kalman Filter

Deep Parikh, Manoranjan Majji

专题命中 机器人多传感器融合 ：sensor fusion(title)

Comments Presented at 46th Rocky Mountain AAS Guidance, Navigation and Control (GN&C) Conference, Breckenridge, CO

In-situ surface porosity prediction in DED (directed energy deposition) printed SS316L parts using multimodal sensor fusion

Adithyaa Karthikeyan, Himanshu Balhara, Abhishek Hanchate, Andreas K Lianos, Satish TS Bukkapatnam

专题命中 机器人多传感器融合 ：sensor fusion(title)