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

EFRI-COPN：对人脑控制手的能力进行逆向工程

• 批准号: 0836042
• 负责人: Francisco Valero-Cuevas
• 金额: $ 200万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-11-01 至 2012-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0836042&HistoricalAwards=false
• 关键词: EFRI; COPN; Reverse; engineering; Human

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.

该项目旨在对人脑控制手部的能力进行逆向工程。 该项目首先将PI先前开发的机器人手与新型敏感皮肤结合起来，并带有一百个仿生触觉传感器。 该项目的主要目标是了解如何实现手的近似最佳控制，执行熟悉但具有挑战性的操作对象的任务。新的、更先进的基于学习的控制算法将在该项目的四个实验平台上开发和测试：（1）仿生手的机器人操作;（2）来自人类手部执行相同任务的记录数据;（3）物理手部的计算机模拟;（4）通过肌腱对尸体手部的计算机控制。该项目将使用相同的算法作为人类运动控制模型，并超越机器人操作的现有技术;这种生物学和工程学的统一方法是COPN主题变革目标的重要组成部分。灵巧机器人手在工业、空间和国家安全方面有着广泛的应用。更好地理解人类如何学会用手更好地工作也将带来更广泛的好处，特别是对残疾人。该小组提出了一个有力的教育和推广计划，利用他们将开发的演示的人类利益方面。