面向网络化具身机器人的边缘多模态智能——PRAI 2026 研讨会

爱科会易· 2026-06-25 · 内容存档(仅供参考,以主办方最新公告为准)

会议简介










        由上海交通大学、IEEE主办,人工智能学院承办的2026年IEEE第九届模式识别与人工智能国际会议 (PRAI 2026)  将于2026年8月14-16日在中国上海隆重举行。

会议论文将收录至 IEEE Xplore 数字图书馆,并确保被 Ei Compendex 核心、Scopus 等主流数据库检索。

        本届会议除了机器人感知、智慧医疗、自动驾驶、联邦学习等12大主题外,特设 “面向网络化具身机器人的边缘多模态智能”研讨会,现面向相关领域的专家学者、研究人员及研究生公开征稿。


Final Call 之后不再延期!

截稿日期:2026年7月5日

通知日期:2026年7月20日










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Workshop Summary: 

This workshop focuses on edge multimodal intelligence for networked embodied robots, a compact intersection of pattern recognition, machine learning, IoT, and robotics. It targets robots that must perceive, reason, and interact in real time under limited computing, energy, privacy, and connectivity conditions. The workshop will discusslightweight multimodal foundation models, on-device and edge inference, federated/continual learning for robot agents, real-time perception-action loops, and trustworthy embodied AI. The goal is to connect PRAI communities in robot perception, IoT applications, and privacy-aware machine learning, and to promote deployable robotic AI systems with measurable perception accuracy, interaction quality, robustness, and resource efficiency.  

  

本研讨会聚焦“面向网络化具身机器人的边缘多模态智能”,定位于模式识别、机器学习、物联网与机器人应用的交叉方向。研讨会重点讨论具身机器人在受限算力、能耗、隐私和网络条件下,如何实现实时感知、推理与交互。核心内容包括轻量化多模态基础模型、端侧/边缘推理、机器人智能体的联邦学习与持续学习、实时感知-决策闭环,以及可信具身智能。本研讨会旨在对接 PRAI 的机器人感知、物联网应用和隐私计算/联邦学习等主题,推动可部署、可评测、可复现的具身智能系统研究。      

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Topics of Interest: 

  • Multimodal Perception and Scene Understanding for Embodied Robots (具身机器人的多模态感知与场景理解)

  • Lightweight Multimodal Foundation Models for On-device and Edge Robotic Agents (端侧/边缘机器人的轻量化多模态基础模型)

  • Federated, Continual, and Collaborative Learning for Networked Robots (网络化机器人的联邦学习、持续学习与协同学习)

  • Real-time Perception-Action Loops and Human-Robot Interaction (实时感知-决策闭环与人机交互)

  • Edge-Cloud Co-inference and Resource-aware Robot Intelligence (边云协同推理与资源感知机器人智能)

  • Trustworthy and Robust Embodied AI Systems (可信与鲁棒具身智能系统)


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Workshop Chairs



Shijing Yuan / 袁诗景

Affiliation: China Telecom Research Institute / 中国电信研究院

Dr. Shijing Yuan is a Researcher at China Telecom. He received his Ph.D. from Shanghai Jiao Tong University as an Outstanding Doctoral Graduate and was previously a Research Assistant at The Hong Kong Polytechnic University. His research focuses on edge intelligence, AI for networking, federated learning, semantic communication, and networked intelligent systems. He has led or participated in MIIT national/ministerial research projects and published first-author papers in IEEE JSAC, TC, TMC, TWC, TCC, TCCN, IoT-J, INFOCOM, ICDCS, ICC, and GLOBECOM. He serves as a Youth Editorial Board Member of Telecommunication Science and Blockchain, and reviews for IEEE IoT-J, TMC, TCC, TC, ToN, and TNSE. His work has also been deployed in a BeiDou-related satellite voice service system.


Gang Liu / 刘刚

Affiliation:China Telecom Research Institute / 中国电信研究院

Dr. Gang Liu received his Ph.D. degree from the School of Electronic and Information Engineering, Beijing Jiaotong University, in 2021. He has published over 10 papers in international journals and conferences, including prestigious venues such as IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, IEEE Wireless Communications Letters, and IEEE GLOBECOM. His current research interests include Information-Centric Networking (ICN), Software-Defined Networking (SDN), Network Function Virtualization (NFV), the Internet of Things (IoT), and 5G/6G communication networks.





Submission Guidelines

作者可在投稿系统中选择与自己文章相关度更高的主题或者专题进行投稿。

* 摘要-只作报告不发表文章;

全文-作报告并发表全文。

* 全文投稿模板:

https://www.prai.net/instruct8.5x11x2.doc (word)

https://www.prai.net/ieee-conference-latex-template.zip (LaTex)

* 投稿系统:

https://www.easychair.org/conferences/?conf=prai2026 (选择 Workshop) 

注意:

  1. 全英文投稿,文章不少于4页。


会议特色与支持

- IEEE出版保障:所有录用并注册的全文将进入IEEE Xplore,EI,Scopus历史检索稳定。

- 优秀论文奖励:专题将评选“最佳论文奖”和“最佳学生论文奖”,颁发证书及奖金。

- 大咖主旨报告:拟邀请相关领域国际知名学者做大会报告及专题特邀报告。

- 上海区位优势:会议将在上海交大和上海创智人工智能学院内举办,交通便利,学术氛围浓厚


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