Robots are basking in the limelight these days, but the possibility of purchasing a Rosie the robot for the home is still a ways off. In fact, robots are used to solve only a few problems today despite their growing popularity. Three panelists at the recent MIT Tech Conference said that’s because programming robots to navigate in the real world, where the unexpected and the accidental are frequent, is complicated.
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“The challenge with those sorts of environments is that there’s a really long tail of strange things that can happen where things go wrong and your robot doesn’t work anymore,” said Stefanie Tellex, assistant professor of engineering and computer science whose Humans to Robots Laboratory at Brown University is working to create collaborative robots. “And it’s really challenging to figure out all of these weird, different edge cases where things don’t quite work.”
In the lab, robot manipulators, or machines built and programmed to pick up objects and place them somewhere else, can accurately pick something up 90% of the time. “That might sound good, but if that robot is in your house picking stuff up for you, then it’s dropping your stuff and breaking your stuff one out of every 10 times,” Tellex said.
Programming robots to solve for the edge cases will require “a combination of better mobility, better sensing and perception,” said Helen Greiner, co-founder iRobot, maker of the Roomba, and founder of CyPhy Works Inc., a drone company. “By sensing, I mean more data coming back; and by perception, I mean the interpretation of that data.”
But that may be really hampering the use of robots to solve more problems has nothing to do with programming robots to sense and interpret the data. Instead, it’s the use cases. “People seem hell-bent on trying to solve problems for everyone just to start,” said Ryan Gariepy, co-founder and CTO at Clearpath Robotics. The autonomous car is a good example, with startups and corporations working on building a level five autonomous vehicle, one that would require no human interaction other than turning the car on and off.
Rather than jump on the level five bandwagon, Gariepy said to start small and look for use cases that can be solved with robotics right now.
He pointed to Bosch and its agricultural robot as an example, and his own company, Clearpath, is bringing industrial self-driving vehicles to the factory. “A factory or warehouse is an indoor city,” he said. Factories have roads, traffic, signals and rules that need to be followed, but, unlike city streets where unpredictability abounds, the factory is a fairly controlled environment.
Clearpath’s technology can be deployed in days, and because the self-driving vehicles operate so similarly to cars (they have turnings signals, for example), training the factory staff is fairly simple. By going the factory route, Gariepy said they’re already in production and making money.