On-board processing for autonomous drone racing: An overview

Abstract

The first Autonomous Drone Racing (ADR) was launched in the IEEE IROS 2016, and continued to be organised in IROS 2017, 2018 and 2019. Inspired by this competition, other international competitions were launched: the AlphaPilot organised by Lockheed Martin in collaboration with the Drone Racing League, and the Game of Drones, organised by Microsoft and Stanford University. A distinctive feature in the IROS ADR and AlphaPilot competitions is that competing drones had to perform on-board processing only. Hence, along these years, teams have presented novel solutions for on-board processing based on a Graphic Processing Unit (GPU), a Field-Programmable Gate Array (FPGA), microcontrollers and embedded computers such as the Odroid or Intel Stick computers. Motivated by the variety of these solutions, the goal of this work is that of providing the reader with a detail description of the hardware used for the competitions, their benefits as much as limitations, including those microchips used in specialised sensors such as the RGB-D and stereo cameras whose data processing is carried out on the sensor itself. It is expected to conclude that GPU will stand out as the best hardware to compute complex processing on-board, in particular due to the use of deep learning not only to address the gate detection problem, but also to address the control and planning tasks involved in this challenge.