Challenges and Implemented Technologies Used in Autonomous Drone Racing
Document Type
Article
Publication Date
1-24-2019
Publication Title
Intelligent Service Robotics
Volume
12
Issue
2
First page number:
137
Last page number:
148
Abstract
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 with onboard resources. 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 challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Five teams which participated in these events present their implemented technologies that cover modified ORB-SLAM, 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.
Keywords
Autonomous drone; Drone racing; Autonomous flight; Autonomous navigation
Disciplines
Electrical and Computer Engineering | Robotics
Language
English
Repository Citation
Moon, H.,
Martinez-Carranza, J.,
Cieslewski, T.,
Faessler, M.,
Falanga, D.,
Simovic, A.,
Scaramuzza, D.,
Li, S.,
Ozo, M.,
De Wagter, C.,
de Croon, G.,
Hwang, S.,
Jung, S.,
Shim, H.,
Kim, H.,
Park, M.,
Au, T.,
Kim, S. J.
(2019).
Challenges and Implemented Technologies Used in Autonomous Drone Racing.
Intelligent Service Robotics, 12(2),
137-148.
Available at:
http://dx.doi.org/10.1007/s11370-018-00271-6