Researchers prep robots for pilot, surgeon roles
Pieter Abbeel, an assistant professor of engineering at the University of California at Berkeley, stated that there are a lot of limitations and a lot of issues to be resolved with regards to realising such advances in robotics. "Now we guide robots through demos, but it would better to let them use YouTube videos to learn on their own," he said.
Researchers typically teach robots 20-30 second tasks today. They aim to enable hierarchical planning systems so robots can break down large jobs into smaller tasks themselves, he said. Other advances are needed in how robots perceive objects without resorting to learned classes and how they use probability to map the space in which they act, he said.
Despite the limits, Abbeel showed robotic helicopters executing an impressive series of difficult maneuvers including stationary flips and rolls. "Anything a pilot can do, our system can learn, and it can go beyond a pilot in being more accurate and repeatable," he said.
Abbeel's team used data from flights of multiple human pilots to create models. It applied hidden Markov models and Kalman filters to refine the models. Still the robots needed to learn each move individually in separate short sessions.
The team also developed methods to teach robots to tie a wide variety of knots and sew a few stitches on large fabrics. The work was in response to a challenge from a colleague to apply artificial intelligence to robotic surgery.
U.S. surgeons guide robotic systems to tie 300,000 knots a year, but so far experiments in autonomous suturing only succeed half the time. "That's not bad, but not the kind of thing you want to go into surgery with," he joked.
Abbeel praised the PR2 robots from Willow Garage he uses in the lab. "They are amazing because they are so reliable and so good to do experiments with," he said.
Figure 1: Doing the laundry: Abbeel's team showed robots folding towels and socks.
- Rick Merritt
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