Research Description
We are studying energy-efficient actuators and model-based control algorithms for lower and upper-limb exoskeletons and prostheses using integrated biomechatronic systems modelling. Environment recognition systems and onboard sensors inform the dynamic controllers, which optimize the movement assistance and regeneration capabilities of these wearable biomechatronic systems for rehabilitation and manufacturing applications.
Student Researchers
• Brock Laschowski
• Ali Nasr
• Keaton Inkol
Keywords and Themes
• Exoskeletons and Prostheses
• Model-Based Control
• Biomechatronic Systems Modelling
• Assistive Technology
• Rehabiliation Engineering
Related Publications
• Laschowski B, McNally W, Wong A, and McPhee J. (2020). Comparative Analysis of Environment Recognition Systems for Control of Lower-Limb Exoskeletons and Prostheses. IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob). DOI: 10.1109/BioRob49111.2020.9224364.
• Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Frontiers in Robotics and AI, 7, 562061. DOI: 10.3389/frobt.2020.562061.
• Laschowski B, Razavian RS, and McPhee J. (2021). Simulation of Stand-to-Sit Biomechanics for Robotic Exoskeletons and Prostheses with Energy Regeneration. IEEE Transactions on Medical Robotics and Bionics. DOI: 10.1109/TMRB.2021.3058323.
• Laschowski B, McNally W, Wong A, and McPhee J. (2021). Computer Vision and Deep Learning for Environment-Adaptive Control of Robotic Lower-Limb Exoskeletons. bioRxiv. DOI: 10.1101/2021.04.02.438126.
