CPS: Small: Generation of natural movement for a multiple degrees-of-freedom robot driven by stochastic cellular actuators

CPS：小型：由随机细胞执行器驱动的多自由度机器人生成自然运动

• 批准号: 0932208
• 负责人: Jun Ueda
• 金额: $ 45.06万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0932208&HistoricalAwards=false
• 关键词: CPS; Small; Generation; natural; movement

The objective of this research is to understand mechanisms for generating natural movements of skeletal mechanisms driven by stochastically-controlled, biologically-inspired actuators. The approach is to verify the hypothesis that the variability associated with high redundancy and the stochastic nature of the actuation is key to generating natural movements. This project seeks to: (i) develop a method to model and characterize actuator array topologies; (ii) develop a method to analyze the force variability of stochastic actuator arrays; (iii) develop an analytical method to generate movements for a robot with multiple degrees of freedom by minimizing the effect of variability; and (iv) demonstrate the validity of the approach through the development of a robotic arm driven by multiple stochastic array actuators.With respect to intellectual merit, the study of inhomogeneous stochastic actuator network topologies inspired by neuromuscular systems could find the "missing links" that bridge the gap between biological natural movements and the ones in artificial systems. Potential results could impact other research areas, including robust computer networks, robust immune systems, and redundant muscle coordination.With respect to broader impacts, a new graduate-level course provides students in engineering and science with a comprehensive and multidisciplinary education in the underlying principles, cutting-edge applications, and societal impacts of biologically-inspired robotics. Outreach activities include an interactive educational program for K-12 students and a workshop for high-school students and their mentors on robot development. International collaboration with Tokyo University of Science, Japan, will be initiated.

本研究的目的是了解随机控制的，生物启发的执行器驱动的骨骼机构产生自然运动的机制。 该方法是为了验证的假设，即与高冗余度和随机性的驱动的变化是产生自然运动的关键。 该项目旨在：（i）开发一种方法来建模和表征致动器阵列拓扑结构;（ii）开发一种方法来分析随机致动器阵列的力可变性;（iii）开发一种分析方法，通过最小化可变性的影响来生成具有多个自由度的机器人的运动;以及（iv）通过开发由多个随机阵列致动器驱动的机器人手臂来证明该方法的有效性。关于智力价值，受神经肌肉系统的启发，对非均匀随机致动器网络拓扑结构的研究可以找到弥补生物自然运动与人工系统运动之间差距的“缺失环节”。 潜在的结果可能会影响其他研究领域，包括强大的计算机网络，强大的免疫系统和冗余肌肉协调。关于更广泛的影响，一个新的研究生课程为工程和科学专业的学生提供了一个全面的多学科教育，包括基本原理，前沿应用和生物启发机器人的社会影响。 外联活动包括为K-12学生举办的互动教育计划，以及为高中生及其导师举办的机器人开发研讨会。 将启动与日本东京理科大学的国际合作。