Collaborative Research: HCC: Medium: Learning to coordinate between human and a robotic prosthesis for symbiotic locomotion

合作研究：HCC：中：学习协调人类和机器人假体之间的共生运动

• 批准号: 2211740
• 负责人: Jennie Si
• 金额: $ 50万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211740&HistoricalAwards=false
• 关键词: Collaborative; Research; HCC; Medium; Learning

Individuals with lower limb amputation depend on assistive devices such as prostheses to restore basic mobility in daily living, and emerging robotic lower limb prostheses are powered and programmable, showing great potential for improved functionality. Yet, the expected benefit of these modern devices has not yet been fully realized, partly because of a lack of seamless coordination between computer controlled artificial joints and human joints in walking. This project will develop novel technology to address this “human-prosthesis symbiotic locomotion problem” which is to say that a human and a wearable robotic lower limb prosthesis interact as collaborating agents and function in unison to achieve a common locomotion performance goal. This research will improve amputees’ walking performance and efficiency while enhancing their sense of prosthesis embodiment and device acceptance, thus dramatically improving their quality of life. This is the first study of human-prosthesis coordination and co-adaptation in locomotion, and will contributes important knowledge in the fields of physical human-robot interaction and human-centered computing. Additional broad impacts will derive from integration of the research into interdisciplinary training of undergraduate and graduate students, in areas including machine learning, human motor control and learning, and rehabilitation engineering. The objective of this project is to create and evaluate a Human-Centered Computing and Control (HC3) framework for improved human-prosthesis walking performance (in terms of symmetrical gait, postural stability, and reduced sense of effort) and prosthesis embodiment, the research to include three thrusts: (1) an innovative formulation of a coordinated human-robot control problem and a learning-based design solution to achieve human-prosthesis symbiotic locomotion, a problem that poses great and new challenges to classical control and existing multiagent reinforcement learning methods; (2) a novel augmented biofeedback interface to enable active human locomotion adaptation to coordinate with the robotic prosthesis; and (3) a new measure of embodiment of intelligent lower limb prostheses in walking based on the concept of biological motion. Furthermore, the HC3 framework will be evaluated on transfemoral amputees walking with a robotic knee prosthesis.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.

下肢截肢患者依靠假肢等辅助设备来恢复日常生活中的基本活动能力，而新兴的机器人下肢假肢是可供电和可编程的，显示出改善功能的巨大潜力。然而，这些现代设备的预期效益尚未完全实现，部分原因是计算机控制的人工关节与人类行走关节之间缺乏无缝协调。该项目将开发新技术来解决“人-假肢共生运动问题”，也就是说，人类和可穿戴机器人下肢假肢作为协作代理相互作用，协同工作，以实现共同的运动性能目标。本研究将提高截肢患者的行走能力和效率，同时增强他们对假肢的体现感和设备的接受度，从而显著改善他们的生活质量。这是第一次研究人-假肢在运动中的协调和共同适应，并将在物理人机交互和以人为本的计算领域贡献重要的知识。在机器学习、人类运动控制和学习以及康复工程等领域，将研究整合到本科生和研究生的跨学科培训中，将产生更广泛的影响。本项目的目标是创建和评估一个以人为中心的计算和控制（HC3）框架，以改善人体假肢的行走性能（在对称步态，姿势稳定性和减少努力感方面）和假肢的体现，研究包括三个重点：(1)创新提出人-机器人协调控制问题和基于学习的设计方案，实现人-假肢共生运动，这是对经典控制和现有多智能体强化学习方法提出的新的重大挑战；(2)一种新型增强生物反馈接口，使人体主动运动适应与机器人假肢协调；(3)基于生物运动概念的智能下肢假肢在行走中的体现新测度。此外，HC3框架将评估经股骨截肢者与机器人膝关节假体行走。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。