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Type Journal Article
Scope Discipline-based scholarship
Title Challenges and implemented technologies used in autonomous drone racing
Organization Unit
Authors
  • Hyungpil Moon
  • Jose Martinez-Carranza
  • Titus Cieslewski
  • Matthias Faessler
  • Davide Falanga
  • Alessandro Simovic
  • Davide Scaramuzza
  • Shuo Li
  • Michael Ozo
  • Christophe De Wagter
  • Guido de Croon
  • Sunyou Hwang
  • Sunggoo Jung
  • Hyunchul Shim
  • Haeryang Kim
  • Minhyuk Park
  • Tsz-Chiu Au
  • Si Jung Kim
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Intelligent Service Robotics
Publisher Springer
Geographical Reach international
ISSN 1861-2776
Volume 12
Number 2
Page Range 137 - 148
Date 2019
Abstract Text Autonomous Drone Racing (ADR) is a challenge for autonomous drones to navigate a cluttered indoor environment without relying on any external sensing in which all the sensing and computing must be done on board. Although no team could complete the whole racing track so far, most successful teams implemented waypoint tracking methods and robust visual recognition of the gates of distinct colors because the complete environmental information was given to participants before the events. In this paper, we introduce the purpose of ADR as a benchmark testing ground for autonomous drone technologies and analyze the challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Six teams that participated in these events present their implemented technologies that cover modifyed ORBSLAM, robust alignment method for waypoints deployment, sensor fusion for motion estimation, deep learning for gate detection and motion control, and stereo-vision for gate detection.
Free access at DOI
Digital Object Identifier 10.1007/s11370-018-00271-6
Other Identification Number merlin-id:20283
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