EFRI-COPN: Reverse-engineering the Human Brain's Ability to Control the Hand

该项目旨在对人脑控制手的能力进行反向工程。该项目首先将PI之前开发的一只机器人手与一种新型的敏感皮肤相结合，这种皮肤带有100个仿生触觉传感器。这个项目的主要目标是了解如何实现灵巧的、近乎最佳的手控制，在操纵对象时执行熟悉但具有挑战性的任务。将在该项目的四个经验试验台上开发和测试新的、更先进的基于学习的控制算法：(1)仿生手的机器人操作；(2)来自执行相同任务的人类手的记录数据；(3)对物理手的计算机模拟；以及(4)通过肌腱对身体手的计算机控制。该项目将使用与人类运动控制模型相同的算法，并超越机器人操纵的当前技术状态；这种生物学和工程学的统一方法是COPN专题变革性目标的重要组成部分。灵巧的机械手在工业、太空和国家安全方面有广泛的可能应用。提高对人类如何学习如何更好地使用双手的理解也将带来更广泛的好处，特别是对残疾人来说。该小组提出了一项积极的教育和外联计划，利用他们将开展的示范活动的人类利益方面。

This project aims to reverse-engineer the human brain's ability to control the hand. The project begins by combining a robotic hand previously developed by the PI with a new type of sensitive skin, with a hundred biomimetic tactile sensors. The main goal of this project is to understand how it is possible to achieve dextrous, approximately optimal control of a hand, performing familiar but challenging tasks in manipulating objects. New, more advanced learning-based control algorithms will be developed and tested on the four empirical testbeds of the project: (1) robotic manipulation by the biomimetic hand; (2) data from recording of human hands performing the same tasks; (3) computer simulations of physical hands; and (4) computer control of cadaver hands via their tendons. The project will use the same algorithms both as models of human motor control and to go beyond the present state of the art in robotic manipulation; this unified approach to biology and engineering is an essential part of the transformative goals of the COPN topic. Dextrous robotic hands have a wide variety of possible applications in industry, space and national security. Improved understanding of how humans can learn to perform better with their hands will also have broader benefits, particularly for the disabled. The team proposes a vigorous plan for education and outreach, capitalizing on the human interest aspects of the demonstrations they will be developing.