Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera

Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly autonomous solution demands performing computationa...

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Autores principales:	Leticia Oyuki Rojas-Perez, Jose Martinez-Carranza
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Autonomous Drone Racing OAK-D CNN deep learning smart camera Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/20855eb2d2ba45ab94c1aff0775ac45f
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id	oai:doaj.org-article:20855eb2d2ba45ab94c1aff0775ac45f
record_format	dspace
spelling	oai:doaj.org-article:20855eb2d2ba45ab94c1aff0775ac45f2021-11-25T18:56:24ZTowards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera10.3390/s212274361424-8220https://doaj.org/article/20855eb2d2ba45ab94c1aff0775ac45f2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7436https://doaj.org/toc/1424-8220Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly autonomous solution demands performing computationally intensive tasks such as gate detection, drone localisation, and state estimation. To this end, other solutions rely on specialised hardware such as graphics processing units (GPUs) whose onboard hardware versions are not as powerful as those available for desktop and server computers. An alternative is to combine specialised hardware with smart sensors capable of processing specific tasks on the chip, alleviating the need for the onboard processor to perform these computations. Motivated by this, we present the initial results of adapting a novel smart camera, known as the OpenCV AI Kit or OAK-D, as part of a solution for the ADR running entirely on board. This smart camera performs neural inference on the chip that does not use a GPU. It can also perform depth estimation with a stereo rig and run neural network models using images from a 4K colour camera as the input. Additionally, seeking to limit the payload to 200 g, we present a new 3D-printed design of the camera’s back case, reducing the original weight 40%, thus enabling the drone to carry it in tandem with a host onboard computer, the Intel Stick compute, where we run a controller based on gate detection. The latter is performed with a neural model running on an OAK-D at an operation frequency of 40 Hz, enabling the drone to fly at a speed of 2 m/s. We deem these initial results promising toward the development of a truly autonomous solution that will run intensive computational tasks fully on board.Leticia Oyuki Rojas-PerezJose Martinez-CarranzaMDPI AGarticleAutonomous Drone RacingOAK-DCNNdeep learningsmart cameraChemical technologyTP1-1185ENSensors, Vol 21, Iss 7436, p 7436 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Autonomous Drone Racing OAK-D CNN deep learning smart camera Chemical technology TP1-1185
spellingShingle	Autonomous Drone Racing OAK-D CNN deep learning smart camera Chemical technology TP1-1185 Leticia Oyuki Rojas-Perez Jose Martinez-Carranza Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
description	Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly autonomous solution demands performing computationally intensive tasks such as gate detection, drone localisation, and state estimation. To this end, other solutions rely on specialised hardware such as graphics processing units (GPUs) whose onboard hardware versions are not as powerful as those available for desktop and server computers. An alternative is to combine specialised hardware with smart sensors capable of processing specific tasks on the chip, alleviating the need for the onboard processor to perform these computations. Motivated by this, we present the initial results of adapting a novel smart camera, known as the OpenCV AI Kit or OAK-D, as part of a solution for the ADR running entirely on board. This smart camera performs neural inference on the chip that does not use a GPU. It can also perform depth estimation with a stereo rig and run neural network models using images from a 4K colour camera as the input. Additionally, seeking to limit the payload to 200 g, we present a new 3D-printed design of the camera’s back case, reducing the original weight 40%, thus enabling the drone to carry it in tandem with a host onboard computer, the Intel Stick compute, where we run a controller based on gate detection. The latter is performed with a neural model running on an OAK-D at an operation frequency of 40 Hz, enabling the drone to fly at a speed of 2 m/s. We deem these initial results promising toward the development of a truly autonomous solution that will run intensive computational tasks fully on board.
format	article
author	Leticia Oyuki Rojas-Perez Jose Martinez-Carranza
author_facet	Leticia Oyuki Rojas-Perez Jose Martinez-Carranza
author_sort	Leticia Oyuki Rojas-Perez
title	Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
title_short	Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
title_full	Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
title_fullStr	Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
title_full_unstemmed	Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera
title_sort	towards autonomous drone racing without gpu using an oak-d smart camera
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/20855eb2d2ba45ab94c1aff0775ac45f
work_keys_str_mv	AT leticiaoyukirojasperez towardsautonomousdroneracingwithoutgpuusinganoakdsmartcamera AT josemartinezcarranza towardsautonomousdroneracingwithoutgpuusinganoakdsmartcamera
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Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera

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