PI: Kemp, Charles C. in collaboration with Reynolds, Matthew S. Proposal Number: 0932592 in collaboration with 0931924
For 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.
