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A Robot Learns To Fly
jerkychew writes: "For those of you that read my last post about the robot escaping its captors, there's more news regarding robots and AI. According to this Reuters article, scientists in Sweden created a robot that essentially 'learned to fly' in just three hours. The robot had no preprogrammed instructions on how to achieve lift, it had to deduce everything through trial and error. Very interesting stuff."
Imagine a day where engineers build cool robots, upload the generic learn-to-do-stuff-with-your limbs program, leave it for a week or so to train up and get optimum calibration, then have it copy it's program onto subsequent batches.
Read _The Practice Effect_ by David Brin. Sci-Fi. It's not a deep read, but entertaining. In an alternate universe where physics are different, the more you do something, the better you get at it. For instance, if you tie a stone to the tip of a stick and pound it against a tree, eventually the stick-stone will turn into a diamond-tipped axe.
It's a stretch, yes, but it's a fun read. You'll love it when the robot (from our world) reappears at the end of the book, after having 'practiced' what it was told to do, unseen, for most of the story.
Software Wars
check out AUVSI's Aerial Robotics Competition
birds, on the other hand, just like any other animal, have to develop such skills.
I don't think you are quite correct here. Evolution has done wonders with the brain and pre-wired some instructions. For instance birds do learn very quickly how not to crash! And there must be some pre-wiring describing how to use air currents for instance.
I'll do it for cheesy poofs.
Likely a similar thing happened with dinosaurs turning into birds. The more webbed ones could jump farther and fall farther without getting hurt, and eventually one of them decided to flap its webs and they became wings. Feathers are just longer, more flexible scales, that make flying even easier.
I do agree that what the robot in the article did was not evolution, it was learning. It wasn't even learning a particularly useful form of 'flying', either; it was attached to vertical poles!
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Seeing is believing; You wouldn't have seen it if you didn't believe it.
What the researchers did was to build a robot that had wings and motors for manipulating them. These could be controlled by a computer. But instead of writing an explicit program telling the robot how to fly, they got the robot to learn how to fly. They did this using some sort of Genetic Algorithm.
Basically, what a GA does is to generate a large population of possible solutions to the problem, then evaluate how good each one is (i.e. measure the lift each one creates in this example) and then to breed good solutions to create successive generations of possible solutions which are (hopefully) better than the previous generations.
Then, once some criterion is met (for example, once the average fitness of your population doesn't change much for several generations), you then select the best solution found so far as being your answer.
In mathematical terms, GAs are stochastic methods of optimising a function; they are typically used when solving the problem using an analytic method would be problematic (i.e. it would take too long etc.).
So it's not really surprising the robot learned to 'fly' -- the researchers just managed to find an optimal sequence of instructions to send to the wings.
The next step would be to get a robot to learn how to hover without the aid of the stabilising poles; then fly from one location to the other; then fly in a straight line in the presence of varying wind etc.
What the research does do is to lend credence to the argument that insects and birds could have evolved, rather than having been 'designed' by some sort of a God.
"The noble art of losing face will one day save the human race"---Hans Blix
Since the robot did not actually fly, it is not a flying robot.
That's Bigboo TAY! TAY!
The article is very light on details, but I assume that this robot is of a variety known as "living robots" or BEAM robots. These robots do not use digital computer components like most people would probably assume. They use simple logic circuits to achieve their goal. And they DO learn in a very limited sense. They have a specific goal in mind (some learn to walk, some learn to seek out light to power their solar cell), and through trial and error they achieve that goal.
That's because you don't know anything about AI research. This is not Lt. Cmdr. Data they're talking about, they're talking about algorithms where they don't have to be given the solution to the problem they are intended to solve at the onset. Rather, they can "learn" the appropriate actions by trial and error. Most (if not all) modern AI research involves this concept in one form or another.
Just because you see the term "AI" on slashdot doesn't mean we're discussing sentience and talking machines. Sometimes it actually refers to the area of Computer Science thusly named.