FW-HTF-P: Human-Robot Collaboration in Disassembly for Future Remanufacturing

FW-HTF-P：人机协作拆卸以实现未来再制造

• 批准号: 1928595
• 负责人: Minghui Zheng
• 金额: $ 15万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928595&HistoricalAwards=false
• 关键词: FW; HTF; Human; Robot; Collaboration

The research objective of this planning project is to advance fundamental knowledge related to human-robot collaboration in product disassembly. Currently, used product disassembly is a labor-intensive process typically conducted manually by human workers. Fostering collaboration between humans and robots in product disassembly will promote end-of-use product recovery, greater sustainability of American manufacturing, profitability of remanufacturing, and better quality of work life for future workers performing disassembly. Technical advances will include development of a computational framework for action planning, human motion prediction, and the control of robotic partners within collaborative human-robot interactions for disassembly. The project team will also perform planning activities (a series of workshops, meetings and a symposium) to explore possible ways to overcome challenges of remanufacturing automation, and to build collaborations between experts in engineering, psychology, sociology, education, marketing, and labor economics as they build a multidisciplinary research team for a long-term FW-HTF research initiative. The proposed pilot research activities will establish an integrated framework that automates disassembly in remanufacturing via the collaboration between human and robots. The framework to be developed will seek to optimize operational cost, disassembly efficiency, and flexibility in handling the variety of dissimilar products coming to remanufacturing sites. The framework consists of three interdependent components: task sequence planning in a human-robot collaborative setting; human behavior prediction; and planning, learning, and control for robots. Additional planning activities, including a symposium, several workshops, meetings, and webinars will foster the integration of multi-disciplinary perspectives from academia and industry. Successful long-term outcomes of this work also include new product design guidelines, new business models of remanufacturing, and new models of their impact on American manufacturing and remanufacturing. The ultimate goal of this project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research proposal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

本规划项目的研究目的是增进产品拆卸过程中人-机器人协作的相关基础知识。目前，二手产品拆卸是一个劳动密集型的过程，通常由人类工人手动进行。促进人类和机器人在产品拆卸方面的合作将促进使用结束的产品回收、美国制造业更大的可持续性、再制造的盈利能力，以及未来执行拆卸的工人更好的工作生活质量。技术进步将包括开发用于行动规划、人类运动预测的计算框架，以及在协作的人-机器人交互中控制机器人伙伴以进行拆卸。项目团队还将执行规划活动(一系列研讨会、会议和研讨会)，以探索克服再制造自动化挑战的可能方法，并在工程、心理学、社会学、教育、市场营销和劳动经济学专家之间建立合作，为FW-HTF长期研究计划建立一个多学科研究团队。拟议的试点研究活动将建立一个综合框架，通过人类和机器人之间的合作，在再制造中实现拆卸自动化。将开发的框架将寻求在处理进入再制造地点的各种不同产品时优化运营成本、拆卸效率和灵活性。该框架由三个相互依赖的部分组成：人-机器人协作环境中的任务序列规划；人类行为预测；以及机器人的规划、学习和控制。其他规划活动，包括一次研讨会、几个讲习班、会议和网络研讨会，将促进学术界和工业界多学科观点的融合。这项工作的成功长期成果还包括新的产品设计指南、再制造的新商业模式，以及它们对美国制造业和再制造的影响的新模式。该项目的最终目标是发展必要的研究人员、研究基础设施和基础工作，以在FW-HTF全面研究计划的层面上扩大研究未来技术、未来工人和未来工作的机会。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Real-Time Receding Horizon Sequence Planner for Disassembly in A Human-Robot Collaboration Setting

用于人机协作环境中拆卸的实时后退地平线序列规划器

• DOI: 10.1115/isfa2020-9657
• 发表时间: 2020
• 期刊: ASME 2020 International Symposium on Flexible Automation (ISFA2020
• 作者: Lee, Meng-Lun;Behdad, Sara;Liang, Xiao;Zheng, Minghui
• 通讯作者: Zheng, Minghui

Robot-Assisted Disassembly Sequence Planning With Real-Time Human Motion Prediction

• DOI: 10.1109/tsmc.2022.3185889
• 发表时间: 2023-01
• 期刊: IEEE Transactions on Systems, Man, and Cybernetics: Systems
• 作者: Meng-Lun Lee;Wansong Liu;S. Behdad;Xiao Liang;Minghui Zheng

Dynamic Model Informed Human Motion Prediction Based on Unscented Kalman Filter

• DOI: 10.1109/tmech.2022.3173167
• 发表时间: 2022-12
• 期刊: IEEE/ASME Transactions on Mechatronics
• 作者: Wansong Liu;Xiao Liang;Minghui Zheng

Disassembly Sequence Planning Considering Human-Robot Collaboration

考虑人机协作的拆卸顺序规划

• DOI: 10.23919/acc45564.2020.9147652
• 发表时间: 2020
• 期刊: 2020 American Control Conference (ACC
• 作者: Lee, Meng-Lun;Behdad, Sara;Liang, Xiao;Zheng, Minghui
• 通讯作者: Zheng, Minghui

Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment

用于对电气和电子设备进行分类的深度学习和机器学习技术

• DOI: 10.1115/detc2021-71403
• 发表时间: 2021
• 期刊: Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
• 作者: Hu, Shuaizhou;Zhang, Xinyao;Liao, Hao-yu;Liang, Xiao;Zheng, Minghui;Behdad, Sara
• 通讯作者: Behdad, Sara