EAGER: Sub-second human-robot synchronization
EAGER: Sub-second human-robot synchronization
批准号:
1345006
负责人:
Gil Weinberg
金额:
$15.6万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-07-01 至 2015-06-30
中文摘要
首席研究员(PI)将探索和测试一些硬件平台和软件算法,其目标是促进亚秒级人机同步。为此,PI将利用音乐媒介,这是对时间要求最高的媒体之一,其中毫秒精度至关重要,因为超过10毫秒的异步操作对听众来说是明显的。具体来说,PI将开发多达三种不同类型的机器人设备,旨在让最近从肘部以下截肢的鼓手能够在他的有机功能手臂和新开发的机器人设备之间进行演奏和同步。此外,他将开发和研究新型预测算法的效率,该算法旨在在人类行为发生之前预测人类行为,并以低延迟和及时的方式触发机器人行为。这项研究将促进我们对各个领域的理解,包括肢体手术的生物力学,预测和预测人类手势的机器学习技术,以及高度精确的肌电机器人设备。更广泛的影响:该项目最终将使大量截肢者受益,他们的生活质量可以通过使用亚秒同步的低延迟机械肢体而得到改善。促进这种精确的亚秒级人机同步还可以提高其他人机交互场景的效率和流程,在这些场景中,人类和机器人必须协作以实现对时间要求很高的共同目标。在这项研究中创造的新颖的基于螺线管的机器人设备也应该有益于一般的音乐家(也就是说,没有残疾的人),他们将能够探索新颖的击鼓技术并创造新颖的音乐效果。
英文摘要
The Principal Investigator (PI) will explore and test a number of hardware platforms and software algorithms whose goal is to facilitate sub-second human-robot synchronization. To this end the PI will utilize the medium of music, one of the most time-demanding media where accuracy in milliseconds is critical because asynchronous operations of more than 10 ms are noticeable by listeners. Specifically, the PI will develop up to three different kinds of robotic devices intended to allow a drummer, whose arm was recently amputated from the elbow down, to play and synchronize between his organic functioning arm and the newly developed robotic devices. In addition, he will develop and investigate the efficiency of novel anticipation algorithms designed to foresee human actions before they take place and trigger robotic actions with low-latency and in a timely manner. This research will advance our understanding in a variety of areas, including the biomechanics of limb operations, machine-learning techniques for the anticipation and prediction of human gestures, and highly accurate myoelectric robotic devices.Broader Impacts: This project will ultimately benefit a large population of amputees whose quality of life could improve through the use of low-latency robotic limbs with sub-second synchronization. Facilitating such accurate sub-second human-robot synchronization could also improve efficiency and flow in other human-robot interaction scenarios where humans and robots must collaborate to achieve time-demanding common goals. The novel solenoid-based robotic device(s) created in this research should also benefit musicians in general (that is to say, who are not disabled), who will be able to explore novel drumming techniques and create novel musical results.
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会议论文
Data Driven Predictive Auditory Cues for Safety and Fluency in Human-Robot Interaction
-
批准号:2240525
-
项目类别:Standard Grant
-
资助金额:$42.23万
-
财政年份:2023
-
负责人:Gil Weinberg
-
依托单位:
NRI: FND: Creating Trust Between Groups of Humans and Robots Using a Novel Music Driven Robotic Emotion Generator
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批准号:1925178
-
项目类别:Standard Grant
-
资助金额:$66.99万
-
财政年份:2019
-
负责人:Gil Weinberg
-
依托单位:
I-Corps: Dexterous Robotic Prosthetic Control Using Deep Learning Pattern Prediction from Ultrasound Signal
-
批准号:1744192
-
项目类别:Standard Grant
-
资助金额:$5.0万
-
财政年份:2017
-
负责人:Gil Weinberg
-
依托单位:
EAGER: Volition Based Anticipatory Control for Time-Critical Brain-Prosthetic Interaction
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批准号:1550397
-
项目类别:Standard Grant
-
资助金额:$17.88万
-
财政年份:2015
-
负责人:Gil Weinberg
-
依托单位:
HCC: Small: Multi Modal Music Intelligence for Robotic Musicianship
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批准号:1017169
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项目类别:Standard Grant
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资助金额:$45.67万
-
财政年份:2010
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负责人:Gil Weinberg
-
依托单位:
HRI: The Robotic Musician - Facilitating Novel Musical Experiences and Outcomes through Human Robot Interaction
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批准号:0713269
-
项目类别:Standard Grant
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资助金额:$44.91万
-
财政年份:2007
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负责人:Gil Weinberg
-
依托单位:
国内基金
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