More advances in the use of data to train autonomous drones in many contexts. Likely to see many more autonomous drone applications. Moving the sensors to the data.
CMU Researchers Train Autonomous Drones Using Cross-Modal Simulated Data
Carnegie Mellon University
Virginia Alvino Young
August 25, 2020
Researchers at Carnegie Mellon University (CMU) developed a two-step approach to teaching autonomous drones perception and action, providing a safe way to deploy drones trained entirely on simulated data into real-world course navigation. In the first step, the researchers used a photorealistic simulator to train the drone on image perception by creating an environment including the drone, a soccer field, and elevated red square gates positioned randomly to create a track. Thousands of randomly generated drone and gate configurations were used to create a large dataset employed in the second step to teach the drone perception of positions and orientations in space. Said CMU's Rogerio Bonatti, "The robot is not learning to recreate going through any specific track. Rather, by strategically directing the simulated drone, it's learning all of the elements and types of movements to race autonomously." .... '
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