Collaborative Research: Assistive Object Manipulation via RFID Guided Robots

合作研究：通过 RFID 引导机器人进行辅助物体操作

• 批准号: 0932592
• 负责人: Charles Kemp
• 金额: $ 20.45万
• 依托单位: Georgia Tech Research Corporation
• 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
• 起止时间: 2009-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0932592&HistoricalAwards=false
• 关键词: Collaborative; Research; Assistive; Object; Manipulation

PI: Kemp, Charles C. in collaboration with Reynolds, Matthew S.Proposal Number: 0932592 in collaboration with 0931924For millions of people, motor impairments diminish quality of life, reduce independence, and increase healthcare costs. Assistive mobile robots that manipulate objects within everyday settings have the potential to improve quality of life by augmenting people's abilities with a cooperative robot. In spite of this promising opportunity, autonomous mobile robots are not yet robust enough for daily operation in real homes. The proposed research directly addresses the challenges of achieving this competence through novel, innovative research that combines RFID-based sensing with autonomous mobile manipulation. Key insights of the proposed work are that the current range of ultra-high frequency passive RFID 'smart labels' makes it feasible for robots to read them from across a room and that their low cost (sub-$0.25) means they can be ubiquitously attached to important objects throughout the home. The unambiguous digital signals available from tagged objects could be profoundly enabling for an assistive robot in three ways which this research will investigate and exploit: (1) scanning a room to provide reliable unique identification of important tagged objects so the robot can provide the user with a menu of available objects and be informed about the objects (e.g., their appearance and appropriate manipulative actions) (2) long-range localization of a tagged object based on its signal characteristics so the robot can approach the object and (3) short-range localization and identification through novel finger-mounted antennas to help the robot manipulate the object, including grasping it and confirming that it has been grasped. We will research these transformative capabilities for assistive robots in the context of object retrieval. Our studies with physically-impaired patients with amyotrophic lateral sclerosis (ALS) from the Emory ALS Center clearly demonstrate that object retrieval via an autonomous mobile robot would be a valued assistive technology, and these capabilities could serve as a foundation upon which other assistive services could be built. We will evaluate the RFID guided robot that results from this research with ALS patients. The robot will include a novel menu-driven user interface that will enable a physically-impaired user to easily select an object and an appropriate delivery method. After this selection, the robot will find, approach, grasp, and deliver the requested object.Intellectual Merit The proposed research will yield novel RFID signal processing strategies and antenna designs, and novel robot localization and manipulation behaviors that significantly advance the state of the art. This will result in a transformative understanding of RFID as a new modality for robot perception. Through our collaboration with patients at the Emory ALS Center we will continue to obtain feedback to guide the research and maximize its real-world value, which will in turn lead to new insights into how robots can best assist this target population.Broader Impacts This research will strengthen the collaboration between researchers at Georgia Tech, researchers at Duke, and patients from the Emory ALS Center. This unique collaboration will accelerate progress in this highly promising area of assistive technology. The proposed research will also promote a new collaboration with the Quality of Life Technology Center at CMU, with whom we will work closely to transfer all developed technologies (hardware and software) via opensource models. We will continue our commitment to the education of under-represented minorities through our participation in Georgia Tech's SURE and Duke's REU programs. By involving all students in the patient studies, this research will enhance their education and increase the pool of talent trained to innovate in this area.

PI: Kemp, Charles C.与Reynolds， Matthew s.合作提案号：0932592与0931924合作对于数百万人来说，运动障碍降低了生活质量，降低了独立性，增加了医疗费用。在日常环境中操作物体的辅助移动机器人有可能通过合作机器人增强人们的能力来提高生活质量。尽管这是一个很有前途的机会，但自主移动机器人还不够强大，无法在现实家庭中进行日常操作。拟议的研究通过将基于rfid的传感与自主移动操作相结合的新颖创新研究，直接解决了实现这一能力的挑战。这项工作的关键见解是，目前超高频无源RFID“智能标签”的范围使机器人可以从房间的另一个角落读取它们，而且它们的低成本（低于0.25美元）意味着它们可以无处不在地附着在家里的重要物体上。从标记对象中获得的明确的数字信号可以从三个方面对辅助机器人产生深远的影响，本研究将调查和利用：(1)扫描房间，为重要的标记物体提供可靠的唯一识别，这样机器人就可以向用户提供可用物体的菜单，并了解这些物体(例如：(2)根据标记对象的信号特征对其进行远程定位，使机器人能够接近该对象；(3)通过新型手指天线进行短距离定位和识别，帮助机器人操纵该对象，包括抓取该对象并确认其已被抓取。我们将在对象检索的背景下研究辅助机器人的这些变革性能力。我们对埃默里肌萎缩性侧索硬化症（ALS）患者的研究清楚地表明，通过自主移动机器人进行物体检索将是一种有价值的辅助技术，这些能力可以作为其他辅助服务的基础。我们将在ALS患者身上评估这项研究产生的RFID引导机器人。该机器人将包括一个新颖的菜单驱动的用户界面，这将使身体受损的用户能够轻松地选择一个对象和适当的交付方法。在此选择之后，机器人将找到，接近，抓住并交付所要求的对象。提出的研究将产生新的RFID信号处理策略和天线设计，以及新的机器人定位和操作行为，这些都将显著推进目前的技术水平。这将导致对RFID作为机器人感知新模式的变革性理解。通过与Emory ALS中心的患者合作，我们将继续获得反馈，以指导研究并最大化其现实价值，这将反过来为机器人如何最好地帮助目标人群提供新的见解。这项研究将加强佐治亚理工学院、杜克大学和埃默里肌萎缩侧索硬化症中心的研究人员之间的合作。这种独特的合作将加速这一极具前景的辅助技术领域的进展。拟议的研究还将促进与CMU生活质量技术中心的新合作，我们将与该中心密切合作，通过开源模式转让所有已开发的技术（硬件和软件）。我们将通过参与佐治亚理工学院的SURE和杜克大学的REU项目，继续致力于弱势群体的教育。通过让所有学生参与患者研究，这项研究将提高他们的教育水平，并增加在这一领域培养创新人才的数量。