Innovating Cutting-Edge Robotics through Collaboration

IEEE Spectrum Video Friday highlighted the collaborative work between the MRRL and FSI Labs on campus that are working to understand how induced vortices can be used to drive downstream motion in a fluid flow. The work is movitaved by applications in underwater assisted gait.

This paper reviews model-based and model-free approaches for continuous prediction of human joint motion using surface electromyography (EMG) signals. The review focuses on approaches that solve the regression problem of continuously decoding motion from EMG as opposed to classification or discrete gesture identification methods. Model-based approaches use physics-based models to capture the dynamics of the muscles; and musculoskeletal geometry to estimate muscle forces and joint torques. Model-free machine learning and deep learning architectures employ training to learn the statistical

Hao Zhang, associate professor in the Manning College of Information and Computer Sciences, has been awarded the U.S. Defense Advanced Research Projects Agency (DARPA) Director’s Fellowship. The prize is awarded to the top performers among recent recipients of the DARPA Young Faculty Award (YFA), a program established to encourage young scientists to pursue high-risk, high-reward research that could result in breakthrough technologies for national security.