TY - JOUR
T1 - Challenges and implemented technologies used in autonomous drone racing
AU - Moon, Hyungpil
AU - Martinez-Carranza, Jose
AU - Cieslewski, Titus
AU - Faessler, Matthias
AU - Falanga, Davide
AU - Li, Shuo
AU - Ozo, Michaël
AU - de Wagter, Christophe
AU - de Croon, Guido
AU - More Authors, null
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Autonomous drone
KW - Drone racing
KW - Autonomous flight
KW - Autonomous navigation
UR - http://www.scopus.com/inward/record.url?scp=85062632735&partnerID=8YFLogxK
U2 - 10.1007/s11370-018-00271-6
DO - 10.1007/s11370-018-00271-6
M3 - Article
SN - 1861-2776
VL - 12
SP - 137
EP - 148
JO - Intelligent service robotics
JF - Intelligent service robotics
IS - 2
ER -