CMU MetaMobility Lab

Enhancing human mobility through robotics, engineering, and AI

We are dedicated to pioneering the next generation wearable robotic technologies that can transcend traditional human physical capabilities, aiming to redefine the boundaries of human mobility.

Here at MetaMobility lab, our focus is on advancing wearable assistive technologies, such as robotic exoskeletons, to enhance human mobility. Our interdisciplinary research program spans across mechatronic designs to integrating artificial intelligence in order to better interpret diverse human motions. The key objective of our lab is to scientifically understand and engineer wearable devices that can improve mobility for individuals with motor impairments. By optimizing control methods of wearable robotic systems through the integration of versatile hardware design, AI algorithms, and insights from human biomechanics, our work aims to develop more intelligent and intuitive wearable robots. Our group's expertise in robotics and AI positions us to tackle the challenges of enhanced human-robot interaction, allowing to create wearable robots that can adapt across various motor tasks and user needs. This effort seeks to establish a foundation for the broader application of wearable interventions in daily life, pushing the boundaries of current mobility assistance technologies.

Latest Publications

I. Kang, D. D. Molinaro, D. Park, D. Lee, P. Kunapuli, K. R. Herrin, A. J. Young, Online Adaptation Framework Enables Personalization of Exoskeleton Assistance During Locomotion in Patients Affected by Stroke, Transactions of Robotics, 2025
M.T. Tagliaferri, L. Campeggi, O.N. Beck, I. Kang, Ground Perturbation Detection via Lower-Limb Kinematic States During Locomotion, 2025 International Conference On Rehabilitation Robotics (ICORR)
J. An, C. Song, E. Halilaj, I. Kang, Optimizing Locomotor Task Sets for Training a Biological Joint Moment Estimator, 2025 International Conference On Rehabilitation Robotics (ICORR)
C. Song, B. Ivanyuk-Skulskyi, A. Krieger, K. Luo, I. Kang, Personalization of Wearable Sensor-Based Joint Kinematics Estimation Using Computer Vision for Hip Exoskeleton Applications, 2025 International Conference On Rehabilitation Robotics (ICORR)
Y. Chiu, U. Lee, C. Song, M. Hu, I. Kang, Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation, 2025 International Conference On Rehabilitation Robotics (ICORR)

Google Sites

Report abuse