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Collaborative Research: CPS: Medium: Closing the Teleoperation Gap: Integrating Scene and Network Understanding for Dexterous Control of Remote Robots

Collaborative Research: CPS: Medium: Closing the Teleoperation Gap: Integrating Scene and Network Understanding for Dexterous Control of Remote Robots
协作研究:CPS:中:缩小远程操作差距:集成场景和网络理解以实现远程机器人的灵巧控制
批准号:
2039070
负责人:
Keith Winstein
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-02-15 至 2025-01-31

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中文摘要
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英文摘要
The aim of this proposal is to enable people to control robots remotely using virtual reality. Using cameras mounted on the robot and a virtual reality headset, a person can see the environment around the robot. However, controlling the robot using existing technologies is hard: there is a time delay because it’s slow to send high quality video over the Internet. In addition, the fidelity of the image is worse than looking through human eyes, with a fixed and narrow view. This proposal will address these limitations by creating a new system which understands the geometry and appearance of the robot’s environment. Instead of sending high-quality video over the Internet, this new system will only send a smaller amount of information about how the environment’s geometry and appearance has changed over time. Further, understanding the geometry and appearance will let us expand the view visible to the person. Overall, these will improve a human’s ability to remotely control the robot by increasing fidelity and responsiveness. We will demonstrate this technology on household tasks, on assembly tasks, and by manipulating small objects.The aim of this proposal is to test the hypothesis that integrating scene and networking understanding can enable efficient transmission and rendering for dexterous control of remote robots through virtual reality interfaces. This system will result in dexterous teleoperation that enables remote human operators to perform complex tasks with remote robot manipulators, such as cleaning a room or repairing a machine. Such tasks have not previously been demonstrated to be teleoperated for two reasons: 1) lack of an intuitive awareness and understanding of the scene around the remote robot, and 2) lack of an effective low-latency interface to control the robot. We will address these problems by creating new scene- and network-aware algorithms which tightly couple sensing, display, interaction and transmission, enabling the operator to quickly and intuitively understand the environment around the robot. This project will research new interfaces which allow the operator to use their hand to directly specify the robot’s end effector pose in six degrees of freedom, combined with spatial- and semantic-object-based models that allow safe high-level commands. This project will evaluate the proposed system by assessing the speed and accuracy of the remote operator’s ability to complete complex tasks, including assembly tasks; the aim will be to complete unstructured assembly tasks that have never been demonstrated to be remotely teleoperated before.This project is in response to the NSF Cyber-Physical Systems 20-563 solicitation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Sidecar: in-network performance enhancements in the age of paranoid transport protocols
Sidecar:偏执传输协议时代的网络内性能增强
DOI: 10.1145/3563766.3564113
发表时间: 2022
期刊: The Twenty-first ACM Workshop on Hot Topics in Networks (HotNets 2022
影响因子: --
作者: [Yuan, Gina, Zhang, David K., Sotoudeh, Matthew, Welzl, Michael, Winstein, Keith]
通讯作者: Winstein, Keith
Computation-centric networking
以计算为中心的网络
DOI: 10.1145/3563766.3564106
发表时间: 2022
期刊: HotNets
影响因子: --
作者: [Deng, Yuhan, Montemayor, Angela, Levy, Amit, Winstein, Keith]
通讯作者: Winstein, Keith
R2E2: low-latency path tracing of terabyte-scale scenes using thousands of cloud CPUs
R2E2:使用数千个云CPU对TB级场景进行低延迟路径追踪
DOI: 10.1145/3528223.3530171
发表时间: 2022
期刊: ACM Transactions on Graphics
影响因子: 6.2
作者: [Fouladi, Sadjad, Shacklett, Brennan, Poms, Fait, Arora, Arjun, Ozdemir, Alex, Raghavan, Deepti, Hanrahan, Pat, Fatahalian, Kayvon, Winstein, Keith]
通讯作者: Winstein, Keith
CAREER: Scarlet: Learned Protocols and Functional Architectures for Low-Latency Internet Video
  • 批准号:
    2045714
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $68.62万
  • 财政年份:
    2021
  • 负责人:
    Keith Winstein
  • 依托单位:
Collaborative Research: PPoSS: Planning: Fixpoint: an operating system and architecture for data-centric computing
  • 批准号:
    2028733
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.5万
  • 财政年份:
    2020
  • 负责人:
    Keith Winstein
  • 依托单位:
CNS Core: Small: Online learning of cross-layer systems for robust and high-performance Internet video transmission
  • 批准号:
    1909212
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2019
  • 负责人:
    Keith Winstein
  • 依托单位:
CSR: Medium: Collaborative Research: GPL: General-Purpose Lambda Computing
  • 批准号:
    1763256
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $80.0万
  • 财政年份:
    2018
  • 负责人:
    Keith Winstein
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)