Human Robot Interaction
Adaptive control of physical human interaction with robotic co-worker
The goal of this research is to develop theories, methods, and tools to understand the mechanisms of neuromotor adaptation in human-robot physical interaction. Human power-assisting systems, e.g., powered lifting devices that aid human operators in manipulating heavy or bulky loads, require physical contact between the operator and machine, creating a coupled dynamic system. This coupled dynamic has been shown to introduce inherent instabilities and performance degradation due to a change in human stiffness; when instability is encountered, a human operator often attempts to control the oscillation by stiffening their arm, which leads to a stiffer system with more instability. Robot co-worker controllers must account for this issue. This research will 1) understand the association between neuromuscular adaptations and system performance limits, 2) develop probabilistic methods to classify and predict the transition of operator’s cognitive and physical states from physiological measures, and 3) integrate this knowledge into a structure of shared human-robot and demonstrate the efficacy in a powered lifting device with real-world constraints. The project will establish control algorithms for robot co-workers that proactively adjust the contact impedance between the operator and robotic manipulator for achieving higher performance and stability.
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Collaborators
Dr. M Shino Shinohara, Applied Physiology, Human Neuromuscular Physiology Lab Dr. Jun Ueda, Mechanical Engineering, Bio-robotics and Human Modeling Lab References
Slow Intermuscular Oscillations are Associated with Cocontraction Steadiness. NE Ahmar, M Shinohara Medicine and science in sports and exercise 49 (9), 1955-1964 Modulations of correlated neural oscillations for improving muscle coactivation control due to repetition and practice. N Ahmar, J Ueda, S M 2016 Congress of International Society of Electrophysiology and Kinesiology Understanding neuromuscular adaptations in human-robot physical interaction for adaptive robot co-workers A Moualeu, Y Razin, N Ahmar, J Ueda, K Feigh, M Shinohara Fourth Annual NSF National Robotic Initiative Meeting The study is supported by the National Science Foundation (IIS-1317718) |
