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Ultra Low Power Deep-Learning-powered Autonomous Nano Drones

  • Authors: Palossi, Daniele; Loquercio, Antonio; Conti, Francesco; Flamand, Eric; Scaramuzza, Davide; Benini, Luca

  Flying in dynamic, urban, highly-populated environments represents an open problem in robotics. State-of-the-art (SoA) autonomous Unmanned Aerial Vehicles (UAVs) employ advanced computer vision techniques based on computationally expensive algorithms, such as Simultaneous Localization and Mapping (SLAM) or Convolutional Neural Networks (CNNs) to navigate in such environments. In the Internet-of-Things (IoT) era, nano-size UAVs capable …

Posted on: September 4, 2018