Control algorithm for teams of robots factors in moving obstacles.
Planning algorithms for teams of robots fall into two categories: centralized algorithms, in which a single computer makes decisions for the whole team, and decentralized algorithms, in which each robot makes its own decisions based on local observations.
With centralized algorithms, if the central computer goes offline, the whole system falls apart. Decentralized algorithms handle erratic communication better, but they’re harder to design, because each robot is essentially guessing what the others will do. Most research on decentralized algorithms has focused on making collective decision-making more reliable and has deferred the problem of avoiding obstacles in the robots’ environment.
At the International Conference on Robotics and Automation in May, MIT researchers will present a new, decentralized planning algorithm for teams of robots that factors in not only stationary obstacles, but moving obstacles, as well. The algorithm also requires significantly less communications bandwidth than existing decentralized algorithms, but preserves strong mathematical guarantees that the robots will avoid collisions.