Szczegóły publikacji
Opis bibliograficzny
A simple vision-based navigation and control strategy for autonomous drone racing / Artur Cyba, Hubert SZOLC, Tomasz KRYJAK // W: MMAR 2021 [Dokument elektroniczny] : 2021 25th international conference on Methods and Models in Automation & Robotics : August 23–26, 2021, Międzyzdroje, Poland. — Wersja do Windows. — Dane tekstowe. — [Piscataway] : IEEE, cop. 2021. — e-ISBN: 978-1-7281-7380-1. — S. 185–190. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 190, Abstr. — Toż. na Dysku Flash. — e-ISBN: 978-1-7281-7379-5
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 135661 |
|---|---|
| Data dodania do BaDAP | 2021-09-13 |
| Tekst źródłowy | URL |
| DOI | 10.1109/MMAR49549.2021.9528463 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
Abstract
In this paper, we present a control system that allows a drone to fly autonomously through a series of gates marked with ArUco tags. A simple and low-cost DJI Tello EDU quadrotor platform was used. Based on the API provided by the manufacturer, we have created a Python application that enables the communication with the drone over WiFi, realises drone positioning based on visual feedback, and generates control. Two control strategies were proposed, compared and critically analysed. In addition, the accuracy of the positioning method used was measured. The application was evaluated on a laptop computer (about 40 fps) and a Nvidia Jetson TX2 embedded GPU platform (about 25 fps). We provide the developed code on GitHub.
