By Kalwinder Kaur
The US research team has developed a robotic set of legs. This is the first model to have biologically precise, complete walking capability, claimed the researchers.
The robot derives human-like walking gait by being in-built with simplified musculoskeletal architecture, neural architecture, and sensory feedback pathways of humans.
Based on the 6 July-dated presentation of IOP Publishing’s Journal of Neural Engineering that describes the biological accuracy of this robot, the researchers discovered the phenomenon that forms the basis of walking in humans. In addition, researchers can formulate theories on the babies’ process of learning to walk, and can also comprehend and make efforts to restore the walking practice of spinal-cord-injury patients.
The central pattern generator (CPG) forms the major part of the human walking system. The CPG is a neural network in the spinal cord’s lumbar region, producing rhythmic muscle signals. Collection of information from various parts of the body that interact with the environment enables CPG to generate as well as control these signals. This enables people to walk involuntarily.
A half-centre is the simplest form of a CPG. It includes only two neurons that send signals alternatively creating a rhythm. The robot includes an artificial half-centre integrated with sensors to return the information to the half-centre. The load sensors can detect the force in the limb while the leg applies pressure on any stepping surface.
According to the assumption of the University of Arizona researchers, babies initially begin walking with a simple half-centre, subsequently followed by learning a network for a difficult walking pattern. This hypothesis can be demonstrated through the fact that a simple half-centre enables walking, i.e., babies show a simple walking pattern on a treadmill even before learning to walk.