Autonomous drone can avoid obstacles even in unfamiliar environments

Andrew Barry, a PhD student at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), has developed a detection algorithm that allows UAVs to avoid objects on their own. Even better, it works even if the planes don’t have existing knowledge/data about a particular location. Barry believes an algorithm faster than existing ones is necessary for truly autonomous drones. LIDAR laser systems, he said, are typically too heavy for small, personal UAVs, while current algorithms are too slow to match their speed. To test his creation, he built a small drone with a 34-inch wingspan and weighs just under a pound using off-the-self parts. It has a camera attached to each wing and two processors similar to the ones found inside smartphones. Unlike other autonomous algorithms that process images for obstacles…


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