权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

EAGER/Collaborative Research: Center-of-Mass Control for Expressive and Effective Movement in Bipedal Robots

EAGER/协作研究：双足机器人富有表现力和有效运动的质心控制

基本信息

批准号：
1701295
负责人：
Amy LaViers
金额：
$ 13.65万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2018-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701295&HistoricalAwards=false
关键词：
EAGER Collaborative Research Center Mass

项目摘要

This EArly-concept Grant for Exploratory Research (EAGER) collaborative project will apply insights from the study of human athletes and dancers to enable similarly effective and expressive movement in humanoid robots. The objective is to create the capability for such movement without duplicating the full complexity and articulation of the human torso. Specifically, the project will implement a novel mechanism for shifting a heavy mass that shifts the robot center of mass independently of limb movements using novel muscle-like actuators, and evaluate the results based on a formal system of movement analysis developed for dance, athletics, and physical therapy. In addition to improving the robot's effectiveness at accomplishing locomotion, i.e., a walking gait, these capabilities will provide new channels for communication between robots and humans, i.e., modulating the style of the walking gait. Humans make unconscious inferences about attitude and intent from observing movement. For example, a robot co-worker will be more effective if its movements communicate trustworthiness and competence to its human partners, and a robot first-responder will be more effective if its movements communicate confidence and leadership during an emergency situation. This project incorporates the interplay of art and technology into outreach activities, such as using dance movements to understand fundamentals of robot locomotion. This project takes a novel approach to generating dynamic walking in a humanoid robot, by exploiting the dynamics of a novel, core-located rolling ball-and-tray actuation mechanism arising from exploration of embodied movement theory. The impedance of the actuator is varied in real time, modulating the robot dynamics to produce qualitatively different excitations. The focus of the project is on controlling the expressive character of robot gait, with explicit comparison to human movement. The goals of the project are to explore the role of center-of-mass control in human walking and to demonstrate the feasibility of the approach for bipedal robotic walking through modeling, simulation, and an initial prototype. The work will model and validate the ball-and-tray actuator via a set of motion primitives designed in accordance with Bartenieff Fundamentals, a formal system of movement analysis. The research team brings together experts in movement science, dynamic walking, and muscle-like actuation. In addition to improving robot performance, this work has the potential to increase the bandwidth of robot-human communications. Expressive movement can convey many different emotional contexts, including urgency, calm, enthusiasm, confidence, et cetera. The ability to engineer these contexts into robot movement has many potential applications in human facing scenarios.

EARLY概念探索性研究资助（EAGER）合作项目将应用人类运动员和舞蹈家研究的见解，使人形机器人能够进行类似的有效和富有表现力的运动。目标是创造这种运动的能力，而不复制人类躯干的全部复杂性和关节。具体来说，该项目将实现一种新的机制，用于转移一个沉重的质量，使用新型的肌肉状致动器独立于肢体运动转移机器人质心，并根据为舞蹈，田径和物理治疗开发的正式运动分析系统评估结果。除了提高机器人完成运动的效率，即，步行步态，这些能力将为机器人和人类之间的通信提供新的渠道，即，调节行走步态的风格。人类通过观察运动，对态度和意图做出无意识的推断。例如，如果机器人的动作向人类伙伴传达了可信度和能力，那么机器人同事将更有效，如果机器人的动作在紧急情况下传达了信心和领导力，那么机器人第一响应者将更有效。该项目将艺术和技术的相互作用融入到推广活动中，例如使用舞蹈动作来了解机器人运动的基本原理。该项目采取了一种新的方法来产生动态行走的人形机器人，通过利用一种新的，核心定位的滚动球和托盘驱动机制的动力学所产生的探索体现运动理论。致动器的阻抗在真实的时间内变化，调制机器人动力学以产生定性不同的激励。该项目的重点是控制机器人步态的表达特征，与人类运动进行明确的比较。该项目的目标是探索质心控制在人类行走中的作用，并通过建模，仿真和初始原型来证明双足机器人行走方法的可行性。这项工作将建模和验证球和托盘致动器通过一组运动基元设计的Bartenieff基本原理，一个正式的运动分析系统。该研究团队汇集了运动科学、动态行走和肌肉样驱动方面的专家。除了提高机器人的性能外，这项工作还有可能增加机器人与人类通信的带宽。表情动作可以传达许多不同的情感背景，包括紧迫感、平静、热情、自信等等。将这些背景设计成机器人运动的能力在面向人类的场景中具有许多潜在的应用。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

DOI：
10.3390/arts7020011
发表时间：
2017-12
期刊：
ArXiv
影响因子：
0
作者：
A. LaViers;Catie Cuan;Madison Heimerdinger;Umer Huzaifa;Catherine Maguire;R. McNish;Alexandra Q. Nilles;I. Pakrasi;Karen Bradley;Kim Brooks Mata;Novoneel Chakraborty;I. Vidrin;Alexander Zurawski
通讯作者：
A. LaViers;Catie Cuan;Madison Heimerdinger;Umer Huzaifa;Catherine Maguire;R. McNish;Alexandra Q. Nilles;I. Pakrasi;Karen Bradley;Kim Brooks Mata;Novoneel Chakraborty;I. Vidrin;Alexander Zurawski

Influence of Environmental Context on Recognition Rates of Stylized Walking Sequences

环境背景对风格化步行序列识别率的影响