多模态信息融合

Zero-Shot Deep Domain Adaptation

Kuan-Chuan Peng, Ziyan Wu, Jan Ernst

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

Comments This paper is accepted to the European Conference on Computer Vision (ECCV), 2018

Robust Navigation In GNSS Degraded Environment Using Graph Optimization

Ryan M. Watson, Jason N. Gross

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

Comments 7 pages, 8 figures, Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017)

iCLAP: Shape Recognition by Combining Proprioception and Touch Sensing

Shan Luo, Wenxuan Mou, Kaspar Althoefer, Hongbin Liu

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

Comments 10 pages, 12 figures, accepted to Autonomous Robots

Generalized Hadamard-Product Fusion Operators for Visual Question Answering

Brendan Duke, Graham W. Taylor

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

Comments 8 pages, 3 figures. To appear in CRV, 2018, 15th Canadian Conference on Computer and Robot Vision

Avoidance of Manual Labeling in Robotic Autonomous Navigation Through Multi-Sensory Semi-Supervised Learning

Junhong Xu, Shangyue Zhu, Hanqing Guo, Shaoen Wu

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

PIVO: Probabilistic Inertial-Visual Odometry for Occlusion-Robust Navigation

Arno Solin, Santiago Cortes, Esa Rahtu, Juho Kannala

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

Comments 10 pages, 4 figures. Paper to be published in WACV 2018

A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder

Daehyung Park, Yuuna Hoshi, Charles C. Kemp

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

Comments 8 pages, under review

Distributed Deep Neural Networks over the Cloud, the Edge and End Devices

Surat Teerapittayanon, Bradley McDanel, H. T. Kung

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

Multi-View Task-Driven Recognition in Visual Sensor Networks

Ali Taalimi, Alireza Rahimpour, Liu Liu, Hairong Qi

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

Comments 5 pages, Accepted in International Conference of Image Processing, 2017

Manifold Relevance Determination: Learning the Latent Space of Robotics

Pete Trautman

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

Mobile Node Localization via Pareto Optimization: Algorithm and Fundamental Performance Limitations

Alessio De Angelis, Carlo Fischione

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

Comments IEEE Journal on Selected Areas in Communications (To Appear), 2015

Vision-based Control of a Soft Robot for Maskless Head and Neck Cancer Radiotherapy

Olalekan P. Ogunmolu, Xuejun Gu, Steve Jiang, Nicholas R. Gans

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

Mobile Robot Navigation on Partially Known Maps using a Fast A Star Algorithm Version

Paul Muntean

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

Fast Optimal Joint Tracking-Registration for Multi-Sensor Systems

Shuqing Zeng

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

Journal ref IEEE T. Instrumentation and Measurement 60(10): 3461-3470 (2011)

Conjugate Variables as a Resource in Signal and Image Processing

Michael Nölle, Martin Suda

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

Comments 22 pages, 2 tables, 6 figures

Computer- and robot-assisted urological surgery

Jocelyne Troccaz

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

Journal ref Progrès en urologie : journal de l'Association française d'urologie et de la Société française d'urologie 16, 2 (2006) 112-20

Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

Jocelyne Troccaz, Michael Baumann, Peter Berkelman, Philippe Cinquin, Vincent Daanen, Antoine Leroy, Maud Marchal, Yohan Payan, Emmanuel Promayon, Sandrine Voros, Stéphane Bart, Michel Bolla, Emmanuel Chartier-Kastler, Jean-Luc Descotes, Andrée Dusserre, Jean-Yves Giraud, Jean-Alexandre Long, Ronan Moalic, Pierre Mozer

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

Journal ref Proceedings of the IEEE 94, 9 (2006) 1665-1677

Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

Pedro U. Lima, Luis M. M. Custodio

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

Journal ref International Journal of Advanced Robotic Systems, ISSN 1729-8806, Volume 1, Number 3 September 2004, pp.141-148

Neural Networks Versus Conventional Filters for Inertial-Sensor-based Attitude Estimation

Daniel Weber, Clemens Gühmann, Thomas Seel

专题命中 机器人多传感器融合 ：sensor fusion(abstract)；information fusion(comments)

Comments accepted for the 23rd International Conference on Information Fusion

Factor Graphs for Heterogeneous Bayesian Decentralized Data Fusion

Ofer Dagan, Nisar R. Ahmed

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

Comments 8 pages, 6 figures, 1 table, submitted to the 24th International Conference on Information Fusion

Journal ref 021 IEEE 24th International Conference on Information Fusion (FUSION), Sun City, South Africa, 2021

Security Vulnerabilities in Software Supply Chain for Autonomous Vehicles

Md Wasiul Haque, Md Erfan, Sagar Dasgupta, Md Rayhanur Rahman, Mizanur Rahman

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

Comments 16 pages, 9 figures, 10 tables

The eXtreme Wavefront Control Toolkit: High-Contrast Imaging Instrument Control for Ground and Space-Based Coronagraphs

极端波前控制工具包（XWCTk）：地基与空间日冕仪的高对比度成像仪器控制

Jared R. Males, Joseph D. Long, Sebastiaan Y. Haffert, Kyle Van Gorkom, Parker Johnson, Rico Landman, Eden McEwen, Olivier Guyon, Vincent Deo, Miles Lucas, Irina Stefan, Katie Twitchell, Jay Kueny, Joshua Liberman, Adam K. Taras, Adam Schilperoort, Matthijs Mars, Ewan S. Douglas, Laird M. Close

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 本文介绍专为MagAO-X ExAO仪器开发的XWCTk软件，基于低延迟工具链，可实现仪器控制、数据保存与压缩，适配地基及未来空间高对比度成像仪器，支持远程操作与自动化开发。

Comments Presented at SPIE Astronomical Telescopes + Instrumentation 2026

Multi-Sensor Alignment for Weather Simulations

用于天气模拟的多传感器对齐

Samsad Alam, Devyani Lambhate, Aditya Mohan, Vishal Kumar, Vaibhav Katewa

机构 * Indian Institute of Science（印度科学研究所） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 研究针对自动驾驶车辆在恶劣天气下的感知问题，提出参考数据集对齐方法和统一天气编辑方法进行多传感器对齐，经实验验证方法有效，能提升3D目标检测模型在不同天气下的鲁棒性。

Embedded Firmware Development for Flight Control, Telemetry, and Video Streaming for DIY UAV Research

用于DIY无人机研究的飞行控制、遥测和视频流的嵌入式固件开发

Ad-Deen Mahbub, Indroneel Roy, Mohammad Kamruzzaman Khan Prince

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 针对低成本无人机，基于双核ESP32-S3微控制器设计优化固件，利用内核任务分配、零拷贝缓冲区等技术，实现飞行控制、遥测和视频传输，经实验评估能提供精确稳定支持，助力DIY项目和研究。

Comments 6 pages, 12 figures, Pre-print

NeuroStrata: Harnessing Neurosymbolic Paradigms for Improved Design, Testability, and Verifiability of Autonomous CPS

NeuroStrata：利用神经符号范式提升自主 CPS 的设计、可测试性和可验证性

Xi Zheng, Ziyang Li, Ivan Ruchkin, Ruzica Piskac, Miroslav Pajic

机构 * Macquarie University（麦考瑞大学） ； University of Pennsylvania（宾夕法尼亚大学） ； University of Florida（佛罗里达大学） ； Yale University（耶鲁大学） ； Duke University（杜克大学） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 NeuroStrata通过神经符号范式提升自主CPS的设计、测试和验证能力，解决不确定性带来的信任和安全认证问题。

Journal ref FSE Companion '25: Companion Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, Trondheim, Norway, June 2025

Deep Temporal Modeling and Ensemble Fusion for Multimodal Emotion Recognition from Physiological Signals

基于生理信号的深度时间建模与集成融合多模态情感识别

Desta Haileselassie Hagos, Saurav Keshari Aryal, Patrick Ymele-Leki, Anietie Andy, Legand L. Burge

机构 * Howard University（霍华德大学） 纠错

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 本研究评估LSTM、TCN和Transformer在WESAD数据集上的多模态情感识别性能，通过消融实验和传感器级早期融合，并采用晚期融合集成策略，最终集成方法达到98.91%准确率和98.56%宏F1分数。

Comments Accepted for publication in the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2026). DOI: https://doi.org/10.1145/3807503.3819363

General Convex Agreement with Near-Optimal Communication

通用凸协议与近最优通信

Marc Dufay, Diana Ghinea, Anton Paramonov

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 本文研究了通用凸协议在长消息场景下的通信复杂度，提出确定性同步协议，实现近最优通信，适用于鲁棒学习和传感器融合等聚合任务。

Comments Working paper

A New Approach to Linear/Nonlinear Distributed Fusion Estimation Problem

一种线性/非线性分布式融合估计问题的新方法

Bo Chen, Guoqiang Hu, Daniel W. C. Ho, Li Yu

专题命中 机器人多传感器融合 ：information fusion(abstract)

AI总结 本文提出了一种新的分布式融合估计方法，针对线性时变系统和非线性系统中的有界噪声问题，通过构造方法和凸优化问题解决估计误差上界和最优加权融合准则设计。

Comments 9 pages, 3 figures

Journal ref IEEE Transactions on Automatic Control, 2018

Anomaly Detection Using Optimally-Placed Micro-PMU Sensors in Distribution Grids

利用最优布置的微PMU传感器进行异常检测

Mahdi Jamei, Anna Scaglione, Ciaran Roberts, Emma Stewart, Sean Peisert, Chuck McParland, Alex McEachern

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 本文提出一种分层架构，用于监控配电网，并建立分析和传感器融合原始方法以检测控制周界的异常行为。通过合成和真实微PMU数据验证了方法的有效性。

Comments This article is submitted to IEEE Transaction on Power System and is currently under the review process

Design of a small-scale prototype for research in airborne wind energy

小型原型机的设计用于空中风能研究

Lorenzo Fagiano, Trevor Marks

专题命中 机器人多传感器融合 ：sensor fusion(abstract)

AI总结 本文提出了一种低成本的小型空中风能原型机设计指南，用于测试传感、执行器和翼型等技术，同时提供了实验装置的详细设计和成本信息。

Comments This manuscript is a preprint of a paper submitted for possible publication on the IEEE/ASME Transactions on Mechatronics and is subject to IEEE Copyright. If accepted, the copy of record will be available at IEEEXplore library: http://ieeexplore.ieee.org/

Journal ref IEEE/ASME Transactions on Mechatronics, Volume:20 , Issue: 1, Pages 166 - 177, 2015