Cooperative Adaptation and Shaping of Human Motor Control through Unstable Physical Human-Robot Interactions

通过不稳定的物理人机交互来协作适应和塑造人类运动控制

• 批准号: 1334389
• 负责人: Jingang Yi
• 金额: $ 32万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1334389&HistoricalAwards=false
• 关键词: Cooperative; Adaptation; Shaping; Human; Motor

The research objective of this project is to establish a learning, modeling and tuning framework of human motor control through unstable physical human-robot interactions (upHRI). Rider-bikebot interactions will be used as an upHRI paradigm to examine a sensorimotor theory for modeling and shaping human motor control relevant to balancing and other functional whole-body motor activities. Bikebot is an actively controlled bicycle-based robot. By perturbing rider's sensorimotor mechanism through controlled steering, velocity, and balancing, bikebot offer a new platform for studying physical human-robot interactions. This project will develop new learning, modeling and control schemes for human motor strategies through rider-bikebot interactions, including (1) the development of the in-situ sensing and actuation design to enable perturbing, extracting and evaluation of human motor skills in upHRI; (2) the novel control-theoretic physical/statistical modeling framework of extracting and characterizing human motor control strategies on reduced-dimensionality embedding manifolds; and (3) the control methodologies to cooperatively adapt and tune the human motor strategies in upHRI. The new knowledge and tools developed in this project will serve as a cornerstone to further advance understanding of general physical HRI and to design new human-inspired control and coordination with other complex robotic systems.If successful, the research outcomes of this project will generate new knowledge, methodologies and enabling tools for designing a broader class of human-in-the-loop control systems. A direct outcome of the proposed research will potentially lead to develop a new bikebot-assisted diagnosis and rehabilitation tool for neurological disorder patients. In a long term, the outcomes of this project will provide potential approaches to engineer the tools for biological discovery. The PIs will distribute systems schematics and design, source code, experimental data, and documentation via the project website so that other groups can learn from this project's outcomes. The PIs will also develop a number of integrated research and education programs to attract students from underrepresented groups into engineering and involve undergraduate students into research.

本计画的研究目标是建立一个借由不稳定的物理人机互动（upHRI）来进行人类运动控制的学习、建模与调整架构。骑手-自行车机器人交互将被用作upHRI范例，以检查用于建模和塑造与平衡和其他功能性全身运动活动相关的人类运动控制的感觉运动理论。Bikebot是一种主动控制的自行车机器人。通过控制转向，速度和平衡来干扰骑手的感觉运动机制，bikebot为研究物理人机交互提供了一个新的平台。该项目将通过骑手-自行车机器人交互为人类运动策略开发新的学习，建模和控制方案，包括（1）开发原位传感和驱动设计，以实现upHRI中人类运动技能的扰动，提取和评估;（2）提出了一种新的控制理论物理/统计建模框架，用于提取和表征人类运动控制策略，维度嵌入流形;和（3）控制方法，以合作地适应和调整人类运动策略upHRI。该项目开发的新知识和工具将成为进一步推进对一般物理HRI的理解并设计新的人类启发控制和与其他复杂机器人系统协调的基石。如果成功，该项目的研究成果将产生新的知识，方法和使能工具，用于设计更广泛的人在回路控制系统。这项研究的直接结果可能会为神经系统疾病患者开发一种新的自行车辅助诊断和康复工具。从长远来看，该项目的成果将为生物发现工具的工程设计提供潜在的方法。PI将通过项目网站分发系统原理图和设计、源代码、实验数据和文档，以便其他小组可以从该项目的成果中学习。PI还将开发一些综合研究和教育计划，以吸引来自代表性不足的群体的学生进入工程领域，并让本科生参与研究。