Collaborative Research: Assistive Object Manipulation via RFID Guided Robots

建议编号：0932592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，并增加了医疗成本。辅助移动机器人在日常环境中操纵物体，通过合作机器人增强人们的能力，有可能提高生活质量。尽管有这个充满希望的机会，但自主移动机器人还不够强大，不足以在真实的家庭中进行日常操作。这项拟议的研究直接解决了通过将基于RFID的传感与自主移动操作相结合的新颖、创新的研究来实现这一能力的挑战。这项拟议工作的关键见解是，目前范围的超高频无源RFID智能标签使机器人能够从房间的另一边读取标签，而且它们的低成本(不到0.25美元)意味着它们可以随处可见地贴在家里的重要物品上。来自标记对象的明确数字信号可以以本研究将调查和利用的三种方式深刻地支持辅助机器人：(1)扫描房间以提供重要标记对象的可靠的唯一标识，从而机器人可以向用户提供可用对象的菜单并被告知对象(例如，它们的外观和适当的操纵动作)(2)基于标记对象的信号特征对标记对象进行远程定位，使得机器人可以接近该对象，以及(3)通过新颖的手指安装的天线来进行近距离定位和识别以帮助机器人操纵该对象，包括抓住它，确认它已经抓住了。我们将在对象检索的背景下研究辅助机器人的这些转换能力。我们对来自Emory ALS中心的肌萎缩侧索硬化症(ALS)身体受损患者的研究清楚地表明，通过自主移动机器人检索对象将是一项有价值的辅助技术，这些能力可以作为建立其他辅助服务的基础。我们将评估这项研究得出的RFID引导机器人在ALS患者中的应用。该机器人将包括一个新颖的菜单驱动的用户界面，将使身体受损的用户能够轻松选择对象和适当的交付方法。经过这次选择，机器人将发现、接近、抓取和交付所请求的对象。智能优点所提出的研究将产生新的RFID信号处理策略和天线设计，以及显著提高技术水平的新的机器人定位和操作行为。这将导致对RFID作为机器人感知的一种新方式的变革性理解。通过我们与埃默里肌萎缩侧索硬化症中心的患者的合作，我们将继续获得反馈，以指导研究并最大限度地发挥其现实价值，这反过来将导致对机器人如何最好地帮助这一目标人群的新见解。布罗德影响这项研究将加强佐治亚理工学院的研究人员、杜克大学的研究人员和埃默里肌萎缩侧索硬化症中心的患者之间的合作。这一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，通过开源模式转移所有已开发的技术(硬件和软件)。我们将通过参加佐治亚理工学院的SURE和杜克大学的REU项目，继续致力于对未被充分代表的少数族裔进行教育。通过让所有学生参与患者研究，这项研究将加强他们的教育，并增加在该领域接受创新培训的人才库。

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.