Researchers train bipedal robots to step lightly over rough terrain

Researchers train bipedal robots to step lightly over rough terrain
Researchers at the Hybrid Robotics Group at UC Berkeley and CMU are hard at work making sure their robots don’t fall over when tiptoeing through rough terrain. Using machine learning and ATRIAS robots, the teams are able to “teach” robots to traverse stepping stones they’ve never seen before.
Their robots, described here, are unique in that they are bipedal and use a mixture of balance and jumping to ensure they don’t tip off the blocks.
“What’s different about our methods is that they allow for dynamic walking as opposed to the slower quasi-static motions that robots tend to use,” write the researchers. “By reasoning about the nonlinearities in the dynamics of the system and by taking advantage of recent advances in optimal and nonlinear control technology, we can specify control objectives and desired robot behaviors in a simple and compact form while providing formal stability and safety guarantees. This means our robots can walk over discrete terrain without slipping or falling over, backed by some neat math and some cool experimental videos.”
The robots are currently “blind” and can’t use visual input to plan their next move. However, with a robot called CASSIE, they will be able to see and feel the stones as they hop along, ensuring that they don’t tip over in the heat of fun… or battle.

Source: Gadgets – techcrunch

Knitting machines power up with computer-generated patterns for 3D shapes

Knitting machines power up with computer-generated patterns for 3D shapes
At last, a use for that industrial knitting machine you bought at a yard sale! Carnegie Mellon researchers have created a method that generates knitting patterns for arbitrary 3D shapes, opening the possibility of “on-demand knitting.” Think 3D printing, but softer.
The idea is actually quite compelling for those of us who are picky about their knitwear. How often have we picked up a knit cap, glove, or scarf only to find it too long, too short, too tight, too loose, etc?
If you fed your sartorial requirements (a 3D mesh) into this system from James McCann and students at CMU’s Textiles Lab, it could quickly spit out a pattern that a knitting machine could follow easily yet is perfectly suited for your purposes.
This has to be done carefully — the machines aren’t the same as human knitters, obviously, and a poorly configured pattern might lead to yarn breaking or jamming the machine. But it’s a lot better than having to build that pattern purl by purl.
With a little more work, “Knitting machines could become as easy to use as 3D printers,” McCann said in a CMU news release.
Of course, it’s unlikely you’ll have one of your own. But maker spaces and designer ateliers (I believe that’s the term) will be more likely to if it’s this easy to create new and perfectly sized garments with them.
McCann and his team will be presenting their research at SIGGRAPH this summer.

Source: Gadgets – techcrunch