MIT’s NanoMap enables Drone Navigation in Uncertain Environments

Companies like Amazon have big ideas for drones that can deliver packages right to your door. But even putting aside the policy issues, programming drones to fly through cluttered spaces like cities is difficult.

Being able to avoid obstacles while traveling at high speeds is computationally complex, especially for small drones that are limited in how much they can carry onboard for real-time processing.

Many existing approaches rely on intricate maps that aim to tell drones exactly where they are relative to obstacles, which isn’t particularly practical in real-world settings with unpredictable objects. If their estimated location is off by even just a small margin, they can easily crash.

With that in mind, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed NanoMap, a system that allows drones to consistently fly 20 miles per hour through dense environments such as forests and warehouses.

The research team says that the system could be used in fields ranging from search and rescue and defense to package delivery and entertainment. It can also be applied to self-driving cars and other forms of autonomous navigation.

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