多模态信息融合

Dynamic Object Detection and Tracking in Construction: A Fisheye Camera and LiDAR Sensor Fusion Model

建筑中的动态目标检测与跟踪：一种鱼眼相机与激光雷达传感器融合模型

Yilong Chen, Huili Huang, Yong K. Cho

机构 * Georgia Institute of Technology（佐治亚理工学院） 纠错

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

AI总结 针对建筑等复杂环境中机器人动态目标检测与跟踪问题，提出融合鱼眼相机与激光雷达传感器的框架，通过在配准点云里识别移动物体、投影坐标分配语义标签并结合图像检测更新卡尔曼滤波器观测，具有高精度、简单且鲁棒的特点。

Comments 4 pages, 8 figures, submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025 Future of Construction Workshop

DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace

DroneShield-AI：一种用于受争议空域中实时自主无人机威胁检测、行为意图分类和群体智能的多模态传感器融合框架

Marius Bayizere

机构 * Independent Researcher（独立研究者） 纠错

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

AI总结 提出DroneShield-AI框架，集成RF信号分类、声学检测、YOLOv8视觉检测等六层处理，通过行为意图分类引擎（BICE）实现六类威胁分类并提前30秒预警，以及图神经网络群体智能模块（GNN-SIM）分析多无人机编队，在低成本硬件上达到96.1%检测精度和142ms延迟。

Comments 23 pages, 6 figures, 11 tables. Code available at https://github.com/bayizeremarius/DroneShield-AI

Uncertainty-Aware Adaptive Sensor Fusion for Autonomous Navigation

不确定性感知的自适应传感器融合用于自主导航

Simegnew Yihunie Alaba, Yuichi Motai

机构 * IEEE 纠错

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

AI总结 提出一种结合无迹卡尔曼滤波（UKF）的混合深度学习方法，通过不确定性感知的自适应融合视觉和惯性特征，提高自主导航中视觉惯性里程计（VIO）的位姿估计精度。

Comments 13 pages

Cross-Level Sensor Fusion with Object Lists via Transformer for 3D Object Detection

基于Transformer的多级传感器融合用于3D目标检测

Xiangzhong Liu, Jiajie Zhang, Hao Shen

机构 * fortiss GmbH（fortiss公司） ； Technical University of Munich（慕尼黑技术大学） 纠错

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

AI总结 本文提出基于Transformer的多级传感器融合方法，通过整合抽象物体列表与原始图像数据，提升3D目标检测性能。

Comments 6 pages, 3 figures, accepted at IV2025

Journal ref 2025 IEEE Intelligent Vehicles Symposium (IV)

Robust sensor fusion against on-vehicle sensor staleness

Meng Fan, Yifan Zuo, Patrick Blaes, Harley Montgomery, Subhasis Das

机构 * Zoox Inc（Zoox公司） 纠错

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

Comments This paper has been accepted by CVPR 2025 Precognition Workshop

Deep Learning-Based Multi-Modal Fusion for Robust Robot Perception and Navigation

Delun Lai, Yeyubei Zhang, Yunchong Liu, Chaojie Li, Huadong Mo

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

Comments 6 pages, 4 figures

Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving

Depanshu Sani, Saket Anand

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

Comments An extended abstract accepted at Young Researchers' Symposium, ICVGIP '24. This extended abstract contains the following: 1. Short summary of our work, SAGA-KF, accepted at ICPR'24. 2. A proposal that was awarded the Qualcomm Innovation Fellowship'24

A Visual Cooperative Localization Method for Airborne Magnetic Surveying Based on a Manifold Sensor Fusion Algorithm Using Lie Groups

Liang Liu, Xiao Hu, Wei Jiang, Guanglei Meng, Zhujun Wang, Taining Zhang

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

Comments 12 pages

GPS-IMU Sensor Fusion for Reliable Autonomous Vehicle Position Estimation

Simegnew Yihunie Alaba

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

Comments 6 pages, 4 figures, and conference

Sensor Fusion by Spatial Encoding for Autonomous Driving

Quoc-Vinh Lai-Dang, Jihui Lee, Bumgeun Park, Dongsoo Har

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

Comments This paper has been accepted for Lecture presentation at the 2023 IEEE SENSORS conference

Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted Data

Maciej K. Wozniak, Viktor Karefjards, Marko Thiel, Patric Jensfelt

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

EcoFusion: Energy-Aware Adaptive Sensor Fusion for Efficient Autonomous Vehicle Perception

Arnav Vaibhav Malawade, Trier Mortlock, Mohammad Abdullah Al Faruque

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

Comments Accepted to be published in the 59th ACM/IEEE Design Automation Conference (DAC 2022)

Multisensor fusion-based digital twin in additive manufacturing for in-situ quality monitoring and defect correction

Lequn Chen, Xiling Yao, Kui Liu, Chaolin Tan, Seung Ki Moon

专题命中 机器人多传感器融合 ：sensor fusion(title,abstract)；分类 eess.IV、eess.SP

Comments 11 pages, 9 figures. Accepted at 24th International Conference on Engineering Design (ICED23)

A Modular Platform For Collaborative, Distributed Sensor Fusion

R. Spencer Hallyburton, Nate Zelter, David Hunt, Kristen Angell, Miroslav Pajic

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

A Multimodal Sensor Fusion Framework Robust to Missing Modalities for Person Recognition

Vijay John, Yasutomo Kawanishi

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

Comments Accepted for ACM Multimedia Asia, 2022

Learning Selective Sensor Fusion for States Estimation

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

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

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). arXiv admin note: text overlap with arXiv:1903.01534

Design of Sensor Fusion Driver Assistance System for Active Pedestrian Safety

I-Hsi Kao, Ya-Zhu Yian, Jian-An Su, Yi-Horng Lai, Jau-Woei Perng, Tung-Li Hsieh, Yi-Shueh Tsai, Min-Shiu Hsieh

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

Comments The 14th International Conference on Automation Technology (Automation 2017), December 8-10, 2017, Kaohsiung, Taiwan

Multi-Camera Sensor Fusion for Visual Odometry using Deep Uncertainty Estimation

Nimet Kaygusuz, Oscar Mendez, Richard Bowden

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

Journal ref 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 2944-2949

Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles

Sammy Sidhu, Linda Wang, Tayyab Naseer, Ashish Malhotra, Jay Chia, Aayush Ahuja, Ella Rasmussen, Qiangui Huang, Ray Gao

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

Comments Presented in Machine Learning for Autonomous Driving Workshop at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia. 11 pages, 8 figures

Multi-view Sensor Fusion by Integrating Model-based Estimation and Graph Learning for Collaborative Object Localization

Peng Gao, Rui Guo, Hongsheng Lu, Hao Zhang

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

Comments Revise several typos and change the Fig2 to be more illustrative

Horus: Using Sensor Fusion to Combine Infrastructure and On-board Sensing to Improve Autonomous Vehicle Safety

Sanjay Seshan

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

Comments Presented at Intel ISEF 2019

Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation

Gregory P. Meyer, Jake Charland, Darshan Hegde, Ankit Laddha, Carlos Vallespi-Gonzalez

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

Comments Accepted for publication at CVPR Workshop on Autonomous Driving 2019

Selective Sensor Fusion for Neural Visual-Inertial Odometry

Changhao Chen, Stefano Rosa, Yishu Miao, Chris Xiaoxuan Lu, Wei Wu, Andrew Markham, Niki Trigoni

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

Comments Accepted by CVPR 2019

Modular Sensor Fusion for Semantic Segmentation

Hermann Blum, Abel Gawel, Roland Siegwart, Cesar Cadena

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

Comments preprint of a paper presented at the IEEE International Conference on Intelligent Robots and Systems 2018

LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry

Ryoichi Ishikawa, Takeshi Oishi, Katsushi Ikeuchi

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

PIRVS: An Advanced Visual-Inertial SLAM System with Flexible Sensor Fusion and Hardware Co-Design

Zhe Zhang, Shaoshan Liu, Grace Tsai, Hongbing Hu, Chen-Chi Chu, Feng Zheng

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

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

推进工业4.0：面向基于3D打印的AI故障检测的多模态传感器融合

Muhammad Fasih Waheed, Shonda Bernadin, Ali Hassan

专题命中 机器人多传感器融合 ：sensor fusion(title,abstract)；分类 eess.SP

AI总结 本研究提出了一种低成本、便携的多模态传感器融合AI系统，用于实时监测FDM 3D打印过程中的故障，提升制造可靠性和可持续性。

Comments International Journal of Engineering Research and Innovation | v17, n2, Fall/Winter 2025

Thinking Fast, Thinking Slow: Adaptive Multimodal Transformer-based Sensor Fusion for Depth Estimation on Ultra-low-power MCUs

快速思考，慢速思考：基于自适应多模态Transformer的超低功耗MCU深度估计传感器融合

Luca Crupi, Lorenzo Lamberti, Giovanni Badaracco, Daniele Allegri, Alessandro Giusti, Daniele Palossi

专题命中 机器人多传感器融合 ：sensor fusion(title,abstract)；分类 eess.IV

AI总结 研究针对超低功耗MCU深度估计问题，提出结合多模态传感器融合与轻量级基于循环Transformer架构的自适应方法，通过令牌传播和增量传感器利用机制平衡能耗与精度，实验证明该方法节能且精度提升显著。

Comments 16 pages, 9 figures, 6 tables. This paper has been accepted for publication in the IEEE Sensors Journal Copyright 2026 IEEE

Inertial Human Motion Capture: From Biomechanics to Recent Sensor Fusion Methods and Back

惯性人体运动捕捉：从生物力学到近期的传感器融合方法再回归

Manon Kok, Ive Weygers, Hassan Osman, Daniel Weber, Ruiyuan Li, Thomas Seel, Ajay Seth

专题命中 机器人多传感器融合 ：sensor fusion(title,abstract)；分类 eess.SP

AI总结 该综述聚焦惯性人体运动捕捉的运动学，介绍确定生物力学问题转化公式的关键方面，指出从IMU估计运动学的挑战及常用方法局限，分享近期有潜力的方法，并通过下肢关节角度估计用例说明相关问题及应用，旨在弥合两社区差距。

Comments 31 pages, 5 figures

Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

高效无监督领域适应回归用于空间-时间传感器融合

Keivan Faghih Niresi, Ismail Nejjar, Olga Fink

机构 * Intelligent Maintenance and Operations Systems Laboratory, EPFL（智能维护与操作系统实验室，瑞士联邦理工学院） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(title,abstract)；分类 eess.SP

AI总结 本文提出一种针对回归任务的高效无监督领域适应方法，通过整合空间-时间图神经网络和源目标域扰动逆Gram矩阵对齐，实现无标注数据下的可扩展领域适应，验证于空气质量监测和EEG信号重建任务，取得最佳性能。

Comments Accepted to IEEE Internet of Things Journal