A team of graduate students in Caltech's Advanced Mechanical Bipedal Experimental Robotics Lab (AMBER), led by Professor Aaron Ames, Bren Professor of Mechanical and Civil Engineering and Control and Dynamical Systems, is developing a new method of generating gaits for robotic assistive devices, which aims to guarantee stability and achieve more natural locomotion for different users.
A paper published in IEEE Robotics and Automation Letters outlines the AMBER team's method and represents the first instance of combining hybrid zero dynamics (HZD)—a mathematical framework for generating stable locomotion—with a musculoskeletal model to control a robotic assistive device for walking. The musculoskeletal model is a computational tool to noninvasively measure the relationship between muscle force and joint contact force. HZD is currently used to create stable walking gaits for bipedal robots, and the muscle model represents how much a muscle stretches or contracts with a given joint configuration.
The team demonstrates its approach on a battery-operated, motorized prosthetic leg. The battery powers the motors, which turn the joints. The motor movement is dictated by the mathematical algorithm developed by the researchers.
To create this mathematical algorithm, the AMBER research team recorded the muscle activity of a person walking with a prosthesis that followed the desired motion generated with HZD alone. This was done using electromyography (EMG), in which one electrode is placed on the skin above a specific muscle. Then the team analyzed the EMG activity of a person walking with a prosthesis that followed the desired motion generated by HZD combined with the muscle models. The latter more closely resembles how a human walks without a prosthesis.








