A researcher from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) has developed an obstacle-detection system that allows a drone to autonomously dip, dart and dive through a tree-filled field at upwards of 30 miles per hour.
“Everyone is building drones these days, but nobody knows how to get them to stop running into things,” says CSAIL PhD student Andrew Barry, who developed the system as part of his thesis with MIT professor Russ Tedrake. “Sensors like lidar are too heavy to put on small aircraft, and creating maps of the environment in advance isn’t practical. If we want drones that can fly quickly and navigate in the real world, we need better, faster algorithms.”
