From vehicle collision avoidance to airline scheduling systems to power supply grids, many of the services we rely on are managed by computers. As these autonomous systems grow in complexity and ubiquity, so too could the ways in which they fail.
Now, MIT engineers have developed an approach that can be paired with any autonomous system, to quickly identify a range of potential failures in that system before they are deployed in the real world. What’s more, the approach can find fixes to the failures, and suggest repairs to avoid system breakdowns.
The team has shown that the approach can root out failures in a variety of simulated autonomous systems, including a small and large power grid network, an aircraft collision avoidance system, a team of rescue drones, and a robotic manipulator. In each of the systems, the new approach, in the form of an automated sampling algorithm, quickly identifies a range of likely failures as well as repairs to avoid those failures.
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