Authors: 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. C.; Kim, S. J.
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 challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Six teams which participated in these events present their implemented technologies that cover modified ORBSLAM, robust alignment method for waypoints deployment, sensor fusion for motion estimation, deep learning for gate detection and motion control, andstereo-vision for gate detection.
- Published in: Intelligent Service Robotics (Volume: 12, Issue: 2)
- DOI: 10.1007/s11370-018-00271-6
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- Date: April 2019