Engineers at University of Arizona have developed a pair of robotic legs that they claim are the world’s most accurate representations of the real things. Though they don’t actually walk on their own and are suspended with a harness, the motion of the various parts of the machine was meticulously modeled on the neuromuscular anatomy of human legs.
Not only was the physical anatomy of the legs reproduced, but the the central pattern generator (CPG), a neural network that triggers repetitive muscle movements, mimicked to activate the robot’s muscle movements. Though there’s a lot of technology here, but the video of the robot below reveals that it still looks a bit clumsy and not yet ready to tango. The hope is that the robot will help researchers learn more about how we learn to walk and may assist in developing new therapies for the disabled and people with gait problems.
Some details of the robot’s underlying architecture from the study abstract in Journal of Neural Engineering:
The body is based on principles derived from human muscular architecture, using muscles on straps to mimic agonist/antagonist muscle action as well as bifunctional muscles. Load sensors in the straps model Golgi tendon organs. The neural architecture is a central pattern generator (CPG) composed of a half-center oscillator combined with phase-modulated reflexes that is simulated using a spiking neural network. We show that the interaction between the reflex system, body dynamics and CPG results in a walking cycle that is entrained to the dynamics of the system. We also show that the CPG helped stabilize the gait against perturbations relative to a purely reflexive system, and compared the joint trajectories to human walking data.
Institute of Physics press release: Most accurate robotic legs mimic human walking gait…
Study abstract in Journal of Neural Engineering: A physical model of sensorimotor interactions during locomotion
(hat tip: Engadget)