Today's industrial robots are remarkably efficient -- as long as they're in a controlled environment where everything is exactly where they expect it to be. But put them in an unfamiliar setting, where they have to think for themselves, and their efficiency plummets. And the difficulty of on-the-fly motion planning increases exponentially with the number of robots involved. For even a simple collaborative task, a team of, say, three autonomous robots might have to think for several hours to come up with a plan of attack.

This week, at the Institute for Electrical and Electronics Engineers' International Conference on Robotics and Automation, a group of MIT researchers were nominated for two best-paper awards for a new algorithm that can significantly reduce robot teams' planning time. The plan the algorithm produces may not be perfectly efficient, but in many cases, the savings in planning time will more than offset the added execution time.

The researchers also tested the viability of their algorithm by using it to guide a crew of three robots in the assembly of a chair.

"We're really excited about the idea of using robots in more extensive ways in manufacturing," says Daniela Rus, the Andrew and Erna Viterbi Professor in MIT's Department of Electrical Engineering and Computer Science, whose group developed the new algorithm. "For this, we need robots that can figure things out for themselves more than current robots do. We see this algorithm as a step in that direction."

Rus is joined on the paper by three researchers in her lab -- first author Mehmet Dogar, a postdoc, and Andrew Spielberg and Stuart Baker, both graduate students in electrical engineering and computer science.