Robotic Human Augmentation

Goals

The EPIC (Exoskeleton and Prosthesis Intelligent Controls) Lab research areas include automation & mechatronics and bioengineering with a focus on the control of powered robotic prostheses and exoskeletons to assist human movement. We implement biological signal processing, intent recognition, and control systems based on EMG and mechanical sensors to improve human-machine capabilities. Our primary goal is to use robotic augmentation technology to restore human movement to individuals with mobility disability.

Issues Involved or Addressed

Lab research is organized into subteams led by graduate student mentors to ensure undergraduates contribute meaningfully to projects.

Human Balance Augmentation Team uses a hip exoskeleton and a CAREN treadmill platform to study and augment balance recovery through biomechanics experiments and machine learning. Programming in Matlab/Python is preferred. Contact: Sofia Arvelo Rojas & Theresa Hardin.

Robotic Hip Exoskeleton Team focuses on intelligent controllers to detect human intent during locomotion using wearable sensors and machine learning. Students gain experience in biomechanics, muscle analysis, energetic cost, and mechatronics. Contact: Dongho Park.

Pediatric Knee Exoskeleton Team works on gait rehabilitation in children using exoskeleton assistance and biofeedback. Undergraduates collect motion capture and EMG data, and help design hardware. Experience in Python, Matlab, CAD, FEA, and biomechanics tools is beneficial. Contact: Siddharth Nathella.

Powered Prosthesis Team develops control strategies for knee and ankle prostheses to improve mobility in amputees. Work involves programming (C++, Python, Matlab, ROS), sensor data analysis, and biomechanics evaluation. Strong CS, EE, BME, or ME backgrounds are desired. Contact: Jason Zhou.

GRAHAM Team (Generalized Robotic Assistance for Handling And Manipulation) aims to reduce strain during manual labor via knee and back exoskeletons and biofeedback. Students assist with human subject testing, machine learning estimators, and hardware/mechatronics development. Skills in embedded programming, mechanical design, and Python/MATLAB/SolidWorks are encouraged. Contact: Christoph Nuesslein.

Ankle Exoskeleton Team designs and tests ankle exoskeletons for augmentation in healthy and clinical populations, focusing on mechanical design, mechatronics, and experimental validation. Matlab and Python experience is preferred. Contact: Matthew Lerner, Ethan Schonhaut, Hangyeol Song.

ARMs Exoskeleton Team develops upper-body wearable devices with smart controllers based on biofeedback. Students participate in biomechanical data collection, hardware design, multi-DOF mechanisms, and mechatronics integration. Experience with OpenSim, motion capture, CAD, FEA, and additive manufacturing is highly preferred. Contact: Carlo Canezo.

Partners/Sponsors

Department of Defense, NSF, CHOA, FDA, GTRI, Lockheed Martin, Rubicon, Nextlex, Vicon