Willow Garage announced it has taught its two-armed, mobile PR2 robot to repeat activities such as pouring water in a glass even if the objects involved are of different sizes (watch video).

That’s second nature for humans, but robots learn by being put through a series of motions and then repeating them precisely—which doesn’t work if the size or distance between the objects has changed. A typical robot is more likely to just pour water on the floor rather than correct for a change in the distance between pitcher and glass.

The key to the ‘bot’s new flexibility is changes to its operating system that allow it to generalize movements and then apply the basic movements it has learned to a situation that’s similar but slightly different—such as when someone has moved the glass or the “water” is in a soda can instead of a pitcher.

PR2 has also demonstrated an ability to find and plug into electric sockets while navigating unaided through eight doors, obstacles in a crowded office environment and humans who suddenly stood in its way.

Willow Garage, an open-source robotics developer, is offering 10 PR2 ‘bots to developers who want to build significantly on the robot's existing abilities.

Researchers at the Max Planck Institute for Dynamics and Self-Organization have announced they’ve harnessed the power of chaos itself to—well, to change the gait with which a robot walks (watch video).

That’s far more difficult than it seems, however.

Robots, like humans, learn different gaits for different challenges (walking up a slope, for example, or down a slope or around obstacles). In humans, those gaits—each a separate set of behaviors learned once and then put back into practice when the situation warrants—are controlled by neural circuits called "central pattern generators" (CPG).

Roboticists have replicated that approach, but have generally needed a separate electronic CPG subsystem for each gait.

The Max Planck researchers created a CPG that, in its natural state, produces a chaotic activity pattern. The pattern changes according to input from the robot’s sensors, and can shift from one to another of several predefined patterns until it finds the one that requires the least energy. In other words, it receives one set of input while walking across a level floor, and the chaotic activity of the CPG is quelled by a stable level of energy output. When it reaches a slope, energy output goes up, and the CPG gets a little chaotic and switches around until it finds the right behavior for the situation.

The next step, researchers say, is to build in memory so the robot can remember what it was doing even after the initial sensory input is gone. Without that memory, it can’t walk over a large obstacle because it would essentially forget what it was doing—actually, what obstacle it has to overcome and the behavior pattern required—once it had climbed partway over and lost sight of the obstacle on which it was now perched.

Despite those advances, Korean developers may be ahead of Willow Garage and Max Planck.

After two years of work, researchers at the Korea Institute of Science and Technology say they’ve created a walking robot maid that’s able to recognize humans, recognize chores that need to be done, clean a home, put clothes in a washing machine and heat food in a microwave.

Which is all very impressive, except for the big pink apron and white skirt they put on it, which kind of detract from the grandeur of it all.