An anonymous reader writes: Traditional obstacle-avoidance software uses images from each camera, and search through the depth-field at multiple distances to determine if an object is in the drone's path. Such approaches are computationally intensive, meaning the drone can't fly faster than 6 miles per hour without specialized processors. PhD student at MIT’s Computer Science and Artificial Intelligence Lab, Andrew Barry realized that at the speeds his drone could travel, the world simply does not change much between frames. Because of that, he could get away with computing just a small subset of measurements — distances of 10 meters away. "As you fly, you push that 10-meter horizon forward, and, as long as your first 10 meters are clear, you can build a full map of the world around you," Barry says.
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