Best Robotic Legs Ever?

A very interesting development has been reported by the Daily Disruption News Desk regarding robotic legs that are claimed to “fully model walking in a biologically accurate manner.” This will come as good news for spinal cord injury patients. Those of us who follow developments in artificial intelligence and robotics will likely take note as well.

I read this account with fascination, and immediately wanted to sketch out my understanding in model form. Extending the colloquialism, to a hammer, everything is a nail – to a systems engineer, everything must be modeled. As conveyed in the article, human walking is controlled by a neural network called the central pattern generator (CPG), which is anatomically located in the lumbar region. It’s purpose is to generate rhythmic muscle signals. The researchers said in its simplest form the CPG can be modeled by a neuron pair that each fire signals in alternating fashion.

To complete this model in addition to the neural architecture, the robot needs muscle-skeleton and sensory feedback components. Roughly, this system can be modeled as shown:

I could be wrong, but this is how I understand the Robotic Leg System!

Co-author of the study Dr Theresa Klein was quoted as saying “…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.”

So, did you catch that? That was quite a surprising statement. Two things are totally counter intuitive to me. First, she said the robot works “without balance.” Does that mean that this robot does not need an “inner ear” to balance? Second, the CPG apparently apparently converts coarse motor commands into forces applied at the hip joint only. The “dangling part of the leg, the lower limb, just follows reflexively, implementing easily programmable commands that simple follow what is happening up stream at the hip.

Another implication of this analysis is that the brain proper plays less of a role in controlling gait that I would have guessed.

This would be a good time to confess that I could be totally wrong in my interpretation of this research and its result; I am learning as I go.

Speaking of which, the CPG model of this study is apparently a good facsimile of how gait is refined from early childhood steps through later improvement during the maturing process. The CPG in humans gets better over time as it learns the best walk to walk by repetition.

This is exciting as I can see similarities between this system and what I am learning in my Udacity.com artificial intelligence class. The evolving understanding of complex bio-mechanical systems as well as advances in AI make this a great time to be a student of such things.

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