A robotic set of legs that is able to fully model walking, in a biologically accurate manner, has been produced by a group of US researchers.
The remarkably human-like walking gait was produced by simplifying the neural architecture, musculoskeletal architecture and sensory feedback pathways of humans, and building them into the robot.
The biological accuracy of their robot has enabled the researchers to further investigate the processes that occur during walking, in humans. “And may bolster theories of how babies learn to walk, as well as helping to understand how spinal-cord-injury patients can recover the ability to walk.”
“A key component of the human walking system is the central pattern generator (CPG). The CPG is a neural network in the lumbar region of the spinal cord that generates rhythmic muscle signals. The CPG produces, and then controls, these signals by gathering information from different parts of the body that are responding to the environment. This is what allows people to walk without needing to think about it.”
“The simplest form of a CPG is a half-centre, which consists of just two neurons that fire signals alternatively, producing a rhythm. The robot contains an artificial half-centre as well as sensors that deliver information back to the half-centre, including load sensors that sense force in the limb when the leg is pressed against a stepping surface.”
Co-author of the study, Dr Theresa Klein, said: “Interestingly, we were able to produce a walking gait, without balance, which mimicked human walking with only a simple half-centre controlling the hips and a set of reflex responses controlling the lower limb.”
“The researchers, from the University of Arizona, hypothesize that babies start off with a simple half-centre, similar to the one developed in this robot, and over time they ‘learn’ a network for a more complex walking pattern. This could explain why babies have been seen to exhibit a simple walking pattern when placed on a treadmill even before they have learnt to walk — a simple half-centre is already in place.”
“This underlying network may also form the core of the CPG and may explain how people with spinal cord injuries can regain walking ability if properly stimulated in the months after the injury,” Dr Klein continued.
The research was just published, July 6, in IOP Publishing’s Journal of Neural Engineering.
The publication of this research follows right on the heels of a July 3rd paper about the creation of an artificial cerebellum.
“Researchers have developed an artificial cerebellum (a biologically-inspired adaptive microcircuit) that controls a robotic arm with human-like precision. The cerebellum is the part of the human brain that controls the locomotor system and coordinates body movements.”
“The developers of the new cerebellar model have obtained a robot that performs automatic learning by extracting the input layer functionalities of the brain cortex. Furthermore, they have developed two control systems that enable accurate and robust control of the robotic arm during object handling.”
“The synergy between the cerebellum and the automatic control system enables robot’s adaptability to changing conditions i.e. the robot can interact with humans. The biologically-inspired architectures used in this model combine the error training approach with predictive adaptive control.”
Source: Institute of Physics (IOP)
Image Credits: Institute of Physics; Markus Breig