Versatile and Dexterous Adaptive Control of Dual-Arm Robots for Personalized Assistance

双臂机器人的多功能灵巧自适应控制，提供个性化协助

• 批准号: EP/L026856/2
• 负责人: Chenguang Yang
• 金额: $ 5.71万
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FL026856%2F2
• 关键词: Versatile; Dexterous; Adaptive; Control; Dual

In the near future, robots are expected to co-habit with human beings and work closely with us in the fields of manufacturing and medicine as well as in other aspects of our daily lives. Unfortunately, most of the current robot control technologies are designed for industrial robots which operate behind safeguarding and for predefined tasks, and thus are not able to cope with the varying tasks in unknown dynamic environments. This project will develop human-like adaptive control techniques to provide versatile and dexterous assistance to humans . In particular, the proposed new control techniques will enable robots to offer personalized assistance to different human users according to their motion patterns. For example, when the robot is interacting with an elderly person, it will automatically slow down; while it would speed up when working with a young man. To achieve these goals, this project will perform physiological studies on human control in the following two aspects: i) apply advanced control theory to analyze bimanually coordinated control strategies of human-beings in various scenarios; ii) investigate how human users develop efficient cooperation with a robot from a machine learning point of view . The establishment of human control models can help us in at least two aspects: developing human-like adaptive controllers with high versatility and dexterity; and personalizing robot control to suit a specific human user. Based on this understanding on human bimanual control and human-human cooperation, this project will: (1) enable the robot to cope with different objects by bimanual haptic exploration; (2) enhance the robustness of robot control in interacting with different human users and in handling various objects; (3) improve robot manipulative dexterity at human-robot interaction scenarios and under geometric constraints/limitations caused by hardware and safety issues; (4) detect motion intention of human user and enhance dexterity with robot joint compliance; (5) introduce a measurement of user experience to quantify how human users are satisfied with the assistance offered by robots; and (6) enable the robot to identify and adapt to motor behavior patterns of a specific human user.In the short term, this project will provide new control technologies for robotics researchers and builders to achieve better manipulation performance in terms of dexterity, versatility, and personalization. In the long run, it will benefit socially and economically to the UK by helping to boost the personal robot industry. It will further make contributions to UK by advancing its technology in the field of Robotics and Autonomous Systems, which is identified by the UK government as one of eight great British Technologies propelling the UK towards future growth.

在不久的将来，机器人有望与人类共同生活，并在制造和医学领域以及我们日常生活的其他方面与我们密切合作。遗憾的是，目前的大多数机器人控制技术都是为工业机器人设计的，这些机器人在保护后执行预定的任务，因此不能应对未知动态环境中的各种任务。该项目将开发类似人类的自适应控制技术，为人类提供多功能和灵巧的帮助。特别是，拟议的新控制技术将使机器人能够根据不同的人类用户的运动模式为他们提供个性化的帮助。例如，当机器人与老年人互动时，它会自动减速；而与年轻人一起工作时，它会加快速度。为了实现这些目标，本项目将从以下两个方面对人类控制进行生理学研究：i)应用先进的控制理论分析人类在不同场景下的双向协调控制策略；ii)从机器学习的角度研究人类用户如何与机器人进行有效的合作。人类控制模型的建立至少可以在两个方面帮助我们：开发具有高度通用性和灵活性的仿人自适应控制器；以及个性化机器人控制以适应特定的人类用户。基于对人类双手控制和人-人合作的理解，本项目将：(1)通过双手触觉探索使机器人能够应对不同的对象；(2)增强机器人控制在与不同人类用户交互和处理各种对象时的健壮性；(3)提高机器人在人机交互场景中以及在硬件和安全问题造成的几何约束/限制下的操作灵活性；(4)检测人类用户的运动意图，并通过机器人关节顺应性来提高灵活性；(5)引入用户体验的测量来量化人类用户对机器人提供的帮助的满意度；使机器人能够识别和适应特定人类用户的运动行为模式。短期内，该项目将为机器人研究人员和建造者提供新的控制技术，以在灵活性、多功能性和个性化方面实现更好的操作性能。从长远来看，它将帮助提振个人机器人行业，从而为英国带来社会和经济上的好处。它将通过推进其在机器人和自主系统领域的技术来进一步为英国做出贡献，该领域被英国政府确定为推动英国未来增长的八大英国技术之一。

项目成果

Towards coordination in human-robot interaction by adaptation of robot's cost function

通过适应机器人的成本函数来实现人机交互的协调

• DOI: 10.1109/icarm.2016.7606928
• 发表时间: 2016
• 作者: Li Y

Mechatronic Design of a Human Robot Coupling Interface for Teaching by Demonstration

• DOI: 10.1016/j.ifacol.2016.10.678
• 发表时间: 2016
• 期刊: IFAC-PapersOnLine
• 作者: P. Liang;Chenguang Yang;Ning Wang;Zhijun Li;Ruifeng Li

Interval Kalman filter based RFID indoor positioning

• DOI: 10.1109/ccdc.2016.7532252
• 发表时间: 2016-05
• 期刊: 2016 Chinese Control and Decision Conference (CCDC)
• 作者: Ning Li;Hongbin Ma;Chenguang Yang

Robust adaptive control for bilateral teleoperation systems with guaranteed parameter estimation

• DOI: 10.1109/icarm.2016.7606890
• 发表时间: 2016
• 期刊: 2016 International Conference on Advanced Robotics and Mechatronics (ICARM)
• 作者: Baorui Jing;J. Na;Guanbin Gao;Chenguang Yang

A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation

表面肌电刚度提取的离散时间算法及其在抗干扰遥操作中的应用

• DOI: 10.1155/2016/6897030
• 发表时间: 2016-04
• 期刊: Discrete Dynamics in Nature and Society
• 影响因子: 1.4
• 作者: Liang, Peidong;Yang, Chenguang;Wang, Ning;Li, Ruifeng
• 通讯作者: Li, Ruifeng