We're going to start with principal bioinspiration.
What we mean in by principal bioinspiration?
Bioinspiration is very popular in many parts of engineering,
it particularly popular in robotics.
We're going to be taking a long view.
We're going to be realizing that humans have been studying animal mobility for
2,000 years since Aristotle wrote his first treatise on the nature of animals.
But we're gonna be focusing on very, very, very specific components of the way in
which human beings have been studying animals which,
of course, ad involves many, many different disciplines.
We're gonna be focusing down on the mechanics.
And so, we're gonna be spending most of our time with the biomechanists.
The people who are zoologists and neuromechanist.
People who try to understand the way the neural system interacts with the muscular
skeletal system.
We'll also be spending a little bit of time with the evolutionary colleges and
a little bit of time with the cognitive animal cognition experts.
But mostly, we'll be dealing with the mechanics
of the body in robots and mechanics of the body, neuro and
musculoskeletal mechanics through most of the weeks of the course.
What we're not gonna do is ever copy.
So we'll be talking about tails, for example, and
we've used tails quite a bit increasingly in our work.
But we never just copy.
So if we were to copy, then we would be in danger of making inferences
about what the animals do that are not really justified.
We'll only be using animal like mechanisms after we consult with the biomechanists.
They explain to us what they understand about what the animals are doing and
why they're doing it.
So we're not going to talk too much about the perils of copying, but
will be inspired in what the extracting principles rather
than copying the morphology or copying the particular behaviors.
Another direction that I would love to take, but
we will not have time to do in this course is that we're not going to talk about
the intelligence components very much.
But embodied autonomy is a fascinating and crucially vital part of robotics,
and we think the animals have as much or more to teach us about embodied autonomy
than they do about the mechanics side where they're already teaching us a lot.
And this is because arguably,
the evolutionary ecologists have taught us that it was active mobility.
It was the beginning of the body's ability to direct itself through space and time.
That's the origin arguably of animal intelligence.
You'd get chess out of animal bodies, but
you'll never get animal mobility out of chess playing machines.
And that's an aspect of artificial intelligence that still is not
well-understood by a lot of my colleagues in computer science and
artificial intelligence in general.
So we're gonna spend a little bit of time, but
not nearly the time that we should spend.
Maybe we'll do that in a subsequent course.
The next set of discussions that we'll have this week are trying to establish
that it really makes sense to focus when we talk about locomotion engineering.
Really, the cutting edge and
the mystery part of locomotion engineering is ground mobility.
And ground mobility, of course is crucial for daily human affairs.
It's crucial for disasters.
We'll talk a little bit about the Sago Mine disaster.
Fukushima disaster a little bit.
All these are places where the ground mobility is lacking in robotics and
it's really impeding our ability to save lives.
We'll talk a little bit about my groups interest in building robots
research assistance for a bench site as you wanna get out of your laboratories and
into the physical world, and into the desert to understand desertification,
and climate change, and that kind of thing.
So, there's clearly a compelling need for mobility.
And when you take that point of view, you quickly realize that wheels and
track are not gonna make it and you better start thinking about legs.
The last set of ideas that we wanna get across in the overview of the whole course
such as what we're gonna be doing in the second of this week,
of this first week is this notion principled engineering.
We want not to just build machines that work accidentally or
work, or we thank our lucky stars that were.
We wanna understand what the mathematical foundations are,
what the physical foundations and then we want a mathematicize those physical
foundations for reasons that I'll try to explain certainly as the semester goes on.
But particularly in the second unit of this week,
I'll try to get that idea present.
We're gonna take the physical foundations o f the exchange of work,
which is what we want our robots to do.
And so it starts with physics and
we're gonna mathematecize those ideas from physics and we're going to try to
generalize using mathematics the kinds of tasks that we can get our robots to do,
and we're gonna try to develop formally guaranteed behaviors, and we're then going
to try to take the mathematical representations of those behaviors.
We're going to try to render them in abstract computational symbols and
then put them together in programming works style compositions to make
the energy exchange that we have our robots doing to have that be programmable
in the sense that information exchange is programmable in computers today.
And that's what I'll try to get across those ideas from the big picture
point of view as this week finishes up.