CPS: Medium: Learning for Control of Synthetic and Cyborg Insects in Uncertain Dynamic Environments
CPS: Medium: Learning for Control of Synthetic and Cyborg Insects in Uncertain Dynamic Environments
批准号:
0931463
负责人:
Pieter Abbeel
金额:
$150.0万
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
项目状态:
已结题
起止时间:
2009-09-01 至 2013-08-31
中文摘要
本研究的目的是使合成和半机器人昆虫在复杂的环境中,如户外或倒塌的建筑物中操作。 由于移动的平台和环境具有显著的不确定性,学习和适应能力是至关重要的。 该方法包括三个主要的推力,使所需的学习和适应:(i)算法的发展,以有效地学习最优控制策略和动态模型,通过共享学习和适应平台和环境之间的各种实例。 (ii)创建可在低成本、低功耗移动的平台上运行的控制学习算法。(iii)在最小数量的真实世界试验中开发在线改进策略性能的算法。拟议的研究将推进实际网络物理系统的学习和适应能力。 所提出的方法将是普遍适用的,并导致一类新的学习和适应系统,能够利用多个任务之间的共享属性,以显着加快学习和适应。这项研究项目的成功将使社会更接近解决移动的、一次性的搜索和救援机器人团队的巨大挑战,这些机器人可以在不确定和新颖的环境中稳健地移动,在灾难情况下寻找幸存者,同时消除救援人员的风险。 该项目将通过研究和课堂作业为本科生和研究生提供跨学科培训,以创建在机器人和生活移动的平台中密切耦合网络和物理方面的系统。 通过SUPERB暑期项目,工程专业的学生将体验学习和机器人技术的研究。
英文摘要
The objective of this research is to enable operation of synthetic andcyborg insects in complicated environments, such as outdoors or in acollapsed building. As the mobile platforms and environment havesignificant uncertainty, learning and adaptation capabilities arecritical. The approach consists of three main thrusts to enable thedesired learning and adaptation: (i) Development of algorithms toefficiently learn optimal control policies and dynamics models throughsharing the learning and adaptation between various instantiations ofplatforms and environments. (ii) Creation of control learningalgorithms which can be run on low-cost, low-power mobile platforms.(iii) Development of algorithms for online improvement of policyperformance in a minimal number of real-world trials. The proposed research will advance learning and adaptationcapabilities of practical cyberphysical systems. The proposedapproach will be generally applicable and lead to a new class oflearning and adapting systems that are able to leverage sharedproperties between multiple tasks to significantly speed uplearning and adaptation. Success in this research project will bring society closer to solvingthe grand challenge of teams of mobile, disposable, search and rescuerobots which can robustly locomote through uncertain and novelenvironments, finding survivors in disaster situations, while removingrisk from rescuers. This project will provide interdisciplinarytraining through research and classwork for undergraduate and graduatestudents in creating systems which intimately couple the cyber andphysical aspects in robotic and living mobile platforms. Through theSUPERB summer program, under-represented students in engineering willexperience research in learning and robotics.
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Collaborative Research: NRI: INT: Scalable, Customizable, Robot Learning with Humans
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批准号:2024675
-
项目类别:Standard Grant
-
资助金额:$70.0万
-
财政年份:2020
-
负责人:Pieter Abbeel
-
依托单位:
Doctoral Student Career Development at the Workshop on the Algorithmic Foundations of Robotics (WAFR)
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批准号:1648643
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项目类别:Standard Grant
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资助金额:$1.0万
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财政年份:2016
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负责人:Pieter Abbeel
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依托单位:
CAREER: Apprenticeship Learning for Robotic Manipulation of Deformable Objects
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批准号:1351028
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2014
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负责人:Pieter Abbeel
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依托单位:
NRI-Large: Collaborative Research: Multilateral Manipulation by Human-Robot Collaborative Systems
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批准号:1227536
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项目类别:Continuing Grant
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资助金额:$116.8万
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财政年份:2012
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负责人:Pieter Abbeel
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依托单位:
RI: Small: Large-Scale Machine Learning for Connectomics
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批准号:1118055
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项目类别:Standard Grant
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资助金额:$45.0万
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财政年份:2011
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负责人:Pieter Abbeel
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依托单位:
海外基金