Abstract: Miniaturizing an autonomous robot is a challenging task – not only the mechanical but also the electrical components have to operate within limited space, payload, and power. Furthermore, the algorithms for autonomous navigation, such as state-of-the-art (SoA) visual navigation deep neural networks (DNNs), are becoming increasingly complex, striving for more flexibility and agility. In this work, we present a sensor-rich, modular, nano-sized Unmanned Aerial Vehicle (UAV), almost as small as a five Swiss Franc coin – called Fünfliber – with a total weight of 18g and 7.2cm in diameter. We conceived our UAV as an open-source hardware robotic platform, controlled by a parallel ultra-low power (PULP) System-on-Chip (SoC) with a wide set of onboard sensors, including three cameras (i.e., infrared, optical flow, and standard QVGA), multiple Time-of-Flight (ToF) sensors, a barometer, and an inertial measurement unit. Our system runs the tasks necessary for a flight controller (sensor acquisition, state estimation, and low-level control), requiring only 10% of the computational resources available aboard, consuming only 9mW – 13x less than an equivalent Cortex M4-based system. Pushing our system at its limit, we can use the remaining onboard computational power for sophisticated autonomous navigation workloads, as we showcase with an SoA DNN running at up to 18Hz, with a total electronics’ power consumption of 271mW.
Abstract: Hanna Muller, Daniele Palossi, Stefan Mach, Francesco Conti, Luca Benini (ETH Zurich, University of Lugano, University of Bologna)