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CHS: Medium: Collaborative Research: Manipulation Assistance for Activities of Daily Living in Everyday Environments

CHS: Medium: Collaborative Research: Manipulation Assistance for Activities of Daily Living in Everyday Environments
CHS:媒介:协作研究:日常环境中日常生活活动的操纵辅助
批准号:
1763878
负责人:
Robert Platt
金额:
$72.48万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2024-07-31

项目摘要

项目成果

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中文摘要
翻译
虽然许多残疾人在家中或其他地方的日常生活活动(ADL)方面需要帮助,但他们非常关心保持独立感,这意味着限制专业或家庭照顾者被要求提供的任务。机器人有可能在这里产生巨大的影响,使人们能够独立生活更长时间。本研究的目标是开发一种机器人轮椅机械手系统(RowMan),包括一个动力轮椅与机器人手臂安装在它,这将有助于其用户执行ADL无论是作为一个辅助设备或自主执行操作任务。在辅助模式下,用户将坐在轮椅上,RoWMan系统根据要求操作物品。而在自主模式下,用户可以要求RowMan自己在房子里导航,取回物品,并按照指示放置它们。该项目将需要开发新的用户界面以及一系列新的机器学习和机器人技术,这些技术将使机器人在非结构化环境中成功自主导航和操纵。为了确保广泛的影响,项目的成果将与用户群体在叉山康复中心进行评估。在最近的焦点小组中,人们发现,用户想要的功能,包括从地板上拿起东西的能力,解锁和打开门的能力,在一个紧凑的货架上操作物品的能力,RoWMan将被设计为使用户能够执行这些类型的任务,重点是两个领域:机器人操作和人机交互。操纵工作将开发新的算法,在非结构化环境中对新物体表现良好。传统上,操纵规划者假设所涉及的对象的形状是预先已知的,或者可以在飞行中估计,但是这些假设在实践中经常会引起问题。这里的重点将是开发基于深度强化学习的新算法,即使在世界的几何形状事先未知的情况下,也可以可靠地执行操作任务。该项目还将支持基于激光笔的新型人机交互研究。最近的研究表明,激光指向对目标用户社区非常有效,因为它使用户能够直接指向环境,而不是在屏幕上,这会引起额外的认知负荷。该项目将开发使用环境背景、激光指向和激光手势相结合来传达复杂意图的新方法。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
While many people with disabilities need help with activities of daily living (ADLs) in their homes or at other locations, they care deeply about maintaining their sense of independence, which implies limiting the tasks that professional or family caregivers are asked to provide. There is the potential for robots to have a huge impact here, by enabling people to live independently for longer. The goal of this research is to develop a robotic wheelchair-manipulator system (RoWMan) consisting of a power wheelchair with a robotic arm mounted on it, that will help its user perform ADLs either as an assistive device or by performing manipulation tasks autonomously. In assistive mode, the user would ride in the wheelchair, with the RoWMan system manipulating items as requested. Whereas in autonomous mode, the user could ask RoWMan to navigate on its own through the house, retrieve items, and place them as directed. This project will necessitate the development of new user interfaces as well as an array of new machine learning and robotics techniques that will enable successful autonomous robotic navigation and manipulation in unstructured environments. To ensure broad impact, project outcomes will be evaluated with a user population at Crotched Mountain Rehabilitation Center.In recent focus groups it was found that users want a number of capabilities, including the ability to pick up something from the floor, the ability to unlock and open a door, the ability to manipulate items on a tightly packed shelf, etc. RoWMan will be designed so as to enable users to perform these sorts of tasks, by focusing on two areas: robotic manipulation and human-robot interaction. The manipulation work will develop new algorithms that perform well with novel objects in unstructured environments. Traditionally, manipulation planners assume that the shapes of the objects involved are known in advance or can be estimated on the fly, but these assumptions often cause problems in practice. The focus here will be to develop new algorithms based on deep reinforcement learning that can perform manipulation tasks reliably even when the geometry of the world is unknown in advance. The project will also support research into a new class of human-robot interaction based on laser pointers. Recent work suggests that laser pointing can be very effective for the target user community because it enables users to point directly in the environment rather than on a screen which induces additional cognitive load. This project will develop new ways of communicating sophisticated intent using a combination of environmental context, laser pointing, and laser gestures.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(17)
专著(0)
科研奖励(0)
会议论文
Learning Manipulation Skills via Hierarchical Spatial Attention
通过分层空间注意力学习操作技能
DOI: 10.1109/tro.2020.2974093
发表时间: 2020
期刊: IEEE Transactions on Robotics
影响因子: 7.8
作者: [Gualtieri, Marcus, Platt, Robert]
通讯作者: Platt, Robert
Robotic Pick-and-Place With Uncertain Object Instance Segmentation and Shape Completion
具有不确定对象实例分割和形状完成的机器人拾取和放置
DOI: --
发表时间: 2021
期刊: IEEE robotics automation letters
影响因子: --
作者: [Marcus Gualtieri, Robert Platt]
通讯作者: Marcus Gualtieri, Robert Platt
DOI: 10.48550/arxiv.2203.04439
发表时间: 2022-03
期刊: ArXiv
影响因子: --
作者: [Dian Wang;R. Walters;Robert W. Platt]
通讯作者: Dian Wang;R. Walters;Robert W. Platt
DOI: 10.1109/icra48891.2023.10161252
发表时间: 2022-10
期刊: 2023 IEEE International Conference on Robotics and Automation (ICRA)
影响因子: --
作者: [Ming Jia;Dian Wang;Guanang Su;David Klee;Xu Zhu;R. Walters;Robert W. Platt]
通讯作者: Ming Jia;Dian Wang;Guanang Su;David Klee;Xu Zhu;R. Walters;Robert W. Platt
16
    FRR: Symmetric Policy Learning for Robotic Manipulation
    • 批准号:
      2314182
    • 项目类别:
      Standard Grant
    • 资助金额:
      $86.67万
    • 财政年份:
      2023
    • 负责人:
      Robert Platt
    • 依托单位:
    CAREER: Robotic Manipulation Using Deep Deictic Reinforcement Learning
    • 批准号:
      1750649
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $49.99万
    • 财政年份:
      2018
    • 负责人:
      Robert Platt
    • 依托单位:
    S&AS: INT: COLLAB: Composable and Verifiable Design for Autonomous Humanoid Robots in Space Missions
    • 批准号:
      1724257
    • 项目类别:
      Standard Grant
    • 资助金额:
      $46.0万
    • 财政年份:
      2017
    • 负责人:
      Robert Platt
    • 依托单位:
    S&AS: FND: COLLAB: Learning Manipulation Skills Using Deep Reinforcement Learning with Domain Transfer
    • 批准号:
      1724191
    • 项目类别:
      Standard Grant
    • 资助金额:
      $30.0万
    • 财政年份:
      2017
    • 负责人:
      Robert Platt
    • 依托单位:
    海外基金