Robotics Rehab Gym Strives for Optimal Learning Outcomes with Human Trainees
UW Department of Electrical and Computer Engineering Associate Professor Domen Novak (left) and Assistant Professor Chao Jiang prepare the Haptic Master robot, that holds people by the arm, guides them and provides force feedback, for an experiment session. PHOTO BY IMAN CHATTERJEE
By Ron Podell
Domen Novak and Chao Jiang are working to develop and evaluate new artificial intelligence (AI) techniques that allow groups of robots to efficiently teach diverse skills to various groups of human learners. Novak, a University of Wyoming associate professor of electrical and computer engineering, is able to do so, thanks to a $565,169 grant from the National Science Foundation through the NSF’s National Robotics Initiative 2.0 program. Jiang, a UW assistant professor of electrical and computer engineering, is a co-investigator on the project. The grant began Oct. 1, 2020, and runs through Sept. 30, 2023. While originally envisioned for motor rehabilitation, the “robotic rehabilitation gym” has potential applications in surgery, sports, education and many other areas. Results of the project could be used for other scenarios where humans learn from autonomous agents. For example, online education, monitored by an AI, could include teaching complex skills, such as various sports, group language therapy, group weight loss exercises and group cognitive training to prevent dementia, Novak says. The new artificial intelligence techniques developed by Novak can be broadly divided into techniques that allow an
AI to dynamically assign human learners to robot “coaches” in order to optimize learning outcome over time; techniques that allow robots to estimate humans’ current skill levels based on noisy sensor or motion data; and techniques that allow human experts, such as therapists, to demonstrate appropriate decision-making to robot AIs, as well as benefit from the automated data analysis techniques available to robots. “This is a fundamental science project, and focuses more on AI development, simulation and proof-of-concept evaluation,” Novak says. “Actual patient work is expected to be limited and occur mostly toward the end of the project. That said, the primary target would be stroke survivors, with multiple people exercising in the same room with a limited array of robots.” “I taught a course, titled Haptic Robotics, in fall 2020 that would have offered direct interaction with these robots had it not been for COVID,” Novak says. “I will try to offer it again over the course of the project and provide hands-on experiences there. This material may be included in other courses as well.” The grant supports two graduate students and one undergraduate student, with potential further undergraduate involvement later in the project. Spring/Summer 2021 • 25
