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

下肢截肢患者依赖假肢等辅助设备来恢复日常生活中的基本活动能力，新兴的机器人下肢假肢具有动力和可编程功能，显示出改善功能的巨大潜力。然而，这些现代设备的预期好处尚未完全实现，部分原因是计算机控制的人工关节与行走时的人类关节之间缺乏无缝协调。该项目将开发新的技术来解决这一“人-假体共生运动问题”，即人类和可穿戴的机器人假肢作为协作剂相互作用，协调一致地发挥作用，以实现共同的运动性能目标。这项研究将改善截肢者的行走能力和效率，同时增强他们的假体体现感和装置接受感，从而显著提高他们的生活质量。这是首次对运动中人-假体协调和协同适应的研究，将在人-机器人物理交互和以人为中心的计算领域贡献重要的知识。将这项研究纳入本科生和研究生的跨学科培训将产生其他广泛的影响，这些领域包括机器学习、人类运动控制和学习以及康复工程。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-机器人的行走性能(在对称步态、姿势稳定性和减少劳动感方面)和假体的实施，研究包括三个方面：(1)创新的人-机器人协调控制问题和基于学习的设计解决方案，以实现人-机器人的共生运动，这对经典控制和现有的多智能体强化学习方法构成了巨大的新的挑战；(2)新的增强型生物反馈接口，使人的主动运动适应与机器人假体协调；(3)基于生物运动的概念，提出了智能假肢在行走中体现的新方法。此外，HC3框架将在使用机器人膝关节假体行走的股骨截肢者身上进行评估。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.