Not long ago, machines grew their skills when programmers put their noses to the grindstone and mercilessly attacked those 104 keys. Machine learning is turning some of that around by replacing the typing with humans demonstrating the actions they want the robot to perform. Suddenly, a factory line-worker can be a robot trainer. This is not new, but a robot needs thousands of examples before it is ready to make an attempt. A new paper from researchers at the University of California, Berkeley, are adding the ability to infer so robots can perform after witnessing a task just one time.
A robotic arm with no learning capability can only be told to go to (X,Y,Z), pick up a thing, and drop it off at (X2, Y2, Z2). Many readers have probably done precisely this in school or with a homemade arm. A learning robot generates those coordinates by observing repeated trials and then copies the trainer and saves the keystrokes. This new method can infer that when the trainer picks up a piece of fruit, and drops it in the red bowl, that the robot should make sure the fruit ends up in the red bowl, not just the location where the red bowl was before.
The ability to infer is built from many smaller lessons, like moving to a location, grasping, and releasing and those are trained with regular machine learning, but the inference is the glue that holds it all together. If this sounds like how we teach children or train workers, then you are probably thinking in the right direction.
Continue reading “Robot Arm is a Fast Learner”
This cat feeder project by [Ben Millam] is fascinating. It all started when he read about a possible explanation for why house cats seem to needlessly explore the same areas around the home. One possibility is that the cat is practicing its mobile hunting skills. The cat is sniffing around, hoping to startle its prey and catch something for dinner. Unfortunately, house cats don’t often get to fulfill this primal desire. [Ben] thought about this problem and came up with a very interesting solution. One that involves hacking an electronic cat feeder, and also hacking his cat’s brain.
First thing’s first. Click past the break to take a look at the demo video and watch [Ben’s] cat hunt for prey. Then watch in amazement as the cat carries its bounty back to the cat feeder to exchange it for some real food.
Continue reading “Hack Your Cat’s Brain to Hunt For Food”
It’s hard to believe that we haven’t covered this one before. If you enjoyed out Barcode challenges from last week, perhaps now is the time for you to take the Python Challenge. We made it through the first 18 levels about a year back but with a total of 33 levels we’re not even close to being finished.
This is an excellent opportunity to learn Python if you’ve never tried it, or test your skills if you’ve already got them. We’d suggest using IDLE which is available as part of the Python language download. Because Python is an interpreted language, IDLE allows you to try out each line of the code you are writing and add it to your program as you get different sections working.
The levels start out fairly easy and require some sniffing around, such as looking at the source code, and dissecting images with Python’s various libraries. As you pass each level, you will be granted access to the Python Challenge forums in order to see how others solved the level. By solving each level and then seeing what different solutions entail you grow your knowledge of the language and reinforce your understanding of how to use it.