ZJUI师生联袂亮相自动化科学与工程国际舞台：高适应性可适配信息物理制造网络专题分论坛举行

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近日，ZJU-UIUC联合研究中心下设的高适应性可适配信息物理制造网络中心（Center for Adaptive, Resilient Cyber-Physical Manufacturing Networks，AR-CyMaN）在2022年IEEE自动化科学与工程国际会议（CASE 2022 ）中，成功组织了一场别开生面的专题分论坛。ZJUI师生在国际舞台上围绕先进制造、人工智能、大数据、自动化等前沿领域，汇报了自己的阶段性研究成果，并同与会专家学者进行了积极交流。

▲ 专题分论坛议程

▲ 成都和墨西哥城线下会场

IEEE自动化科学与工程国际会议是IEEE机器人与自动化协会旗下的旗舰会议，是自动化领域研究者和实践者交流工作的良好国际化平台，也已发展为业界规格最高、规模最大的学术交流与成果展示平台。该会议每年举办一次，今年在墨西哥城举行的同时，也在中国成都举办分会场会议，还设置了线上参与的渠道，三线同步互动，保障全球与会者深度交流。

高适应性可适配信息物理制造网络专题分论坛是由AR-CyMaN中心带头人发起，旨在鼓励成员间的相互交流激发，并在高适应性可适配信息物理制造网络领域创造更多精彩，攻克更多困难。专题分论坛由AR-CyMaN 中心主任、ZJUI教授王宏伟主持，AR-CyMaN 中心联合主任、ZJUI助理教授杨量景联合主持。此次专题分论坛希望通过科技创新，赋能先进制造业，从而刺激创新创业和产业发展。具体而言，AR-CyMaN致力于研究“以自主硬软件交互实现可验证的、安全的制造过程”“通过管理使用网络和数据优化性能”“对低层、高层决策和控制的持续分析和学习”“以动态适应需求和检测到的错误或风险保障可适配”四大议题。

▲ 专题分论坛报告论文

六场精彩纷呈的主题报告，吸引了墨西哥城、成都现场及在线平台上世界各地的与会学者。其中绝大部分的报告，都是ZJUI师生的联袂研究成果，此次专题分论坛也成为了ZJUI师生展示相关研究进展，亮相国际舞台的卓越平台。论坛中闪耀的关于前沿技术的思考和创新，也引得与会者展开了富有成效的积极研讨。

▲ 王铁信同学（二年级博士生）成都会场报告：Self-Recalibrating Micromanipulator System for Resilient Robotic Vision-Based Control；同是另一篇special session paper（Universal Self-Calibrating Vision-Based Robotic Micromanipulator）的第一作者

▲ 专题分论坛线上报告与讨论

通过举办此次专题分论坛，ZJUI师生聚焦先进制造、人工智能、大数据、自动化等技术前沿，深度参与到国际高水平自动化会议中，加强了同国内外自动化领域专家学者及产业界人士的交流与合作，提升了AR-CyMaN和ZJUI在相关领域的知名度提升城市国际影响力。

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On Aug 23, 2022, the Center for Adaptive, Resilient Cyber-Physical Manufacturing Networks (AR-CyMaN) successfully organized a special session on Adaptive and Resilient Cyber-Physical Manufacturing Networks in the 18th IEEE International Conference on Automation Science and Engineering (CASE 2022).

CASE 2022 is the flagship conference of the IEEE Robotics & Automation Society, which provides a primary international forum for automation researchers and practitioners to present and discuss their work. This year, the conference was held in Mexico City with satellite site at Chengdu, China and hybrid online platform to accommodate participation from all parts of the world.

Initiated by the center’s leading researchers, this special session aims to encourage more interesting research based on the collaborations between the center’s members, and is dedicated for exchanging wonderful ideas on adaptive and resilient cyber-physical manufacturing networks. It explored frameworks that make advanced manufacturing more capable, accessible, and democratic to spur innovation and enterprise. Specifically, we aim to consider: (1) Interactions between autonomous hardware and software to produce verifiable and safe manufacturing processes; (2) The curation and use of networks and data to optimize performance; (3) Continuous analysis and learning for both low- and high-level decision-making and control; and (4) On-the-fly adaptation to changing needs and detected errors or risks to ensure resilience.

This special session was chaired by Prof. Hongwei Wang and co-chaired by Asst. Prof. Liangjing Yang, who are the Lead and Co-lead of the Center for Ar-CyMaN, respectively. Featuring six exciting presentations, the session was filled with fruitful exchange of comments and active discussion amongst conference attendees around the world gathered in Mexico City, Chengdu City and Online platform.

Papers presented in the special session:

[1]     Towards Cloud-Facilitated Remote Resource Sharing and Collaborative Workflow Design in Factory Robot Applications

Tengyue Wang, Songjie Xiao, Ricardo Toro Santamaria, Placid Ferreira, Liangjing Yang*

[2]     Knowledge Driven Technologies for Digital Twins in Cyber-Physical Manufacturing Networks: A Review

Mengxuan Li, Ke Ma, Haonan Chen, Tianqing Zhang, Tengyue Wang, Liangjing Yang, Driggs-Campbell Katherine, Hongwei Wang*

[3]     Universal Self-Calibrating Vision-Based Robotic Micromanipulator in the special session.

Tiexin Wang, Tanhong Pu, Haoyu Li, Liangjing Yang*

[4]     Computer Vision Aided Hidden Defects Detection in Additively Manufactured Parts

Tianxiang Hu, Miles Bimrose, Davis McGregor, Jiongxin Wang, Sameh Tawfick, Shao Chenhui, William King, Zuozhu Liu*

[5]     Digital Twin Framework for Reconfiguration Management

Birte Caesar*, Dawn Tilbury, Kira Barton, Alexander Fay

[6]     Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration

Zhe Huang, Ye-ji Mun, Xiang Li, Yiqing Xi, Ninghan Zhong, Weihang Liang, Junyi Geng, Tan Chen Driggs-Campbell Katherine*

图文 | 杨量景课题组供稿  

本期编辑 | 张旖  责任编辑 | 张旖

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