The GRIFFIN perception dataset: Bridging the gap between flapping-wing flight and robotic perception

The development of automatic perception systems and techniques for bio-inspired flapping-wing robots is severely hampered by the high technical complexity of these platforms and the installation of onboard sensors and electronics. Besides, flapping-wing robot perception suffers from high vibration l...

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Detalles Bibliográficos
Autores: Rodríguez-Gómez, J.P., Tapia, Raúl, Paneque, Julio L., Grau, Pedro, Gómez Eguiluz, Augusto, Martínez de Dios, José Ramiro, Ollero Baturone, Aníbal
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/137564
Acceso en línea:https://hdl.handle.net/11441/137564
https://doi.org/10.1109/LRA.2021.3056348
Access Level:acceso abierto
Palabra clave:Data sets for robotic vision
Vision-based navigation
Flappingwing robots
Event-based cameras
Descripción
Sumario:The development of automatic perception systems and techniques for bio-inspired flapping-wing robots is severely hampered by the high technical complexity of these platforms and the installation of onboard sensors and electronics. Besides, flapping-wing robot perception suffers from high vibration levels and abrupt movements during flight, which cause motion blur and strong changes in lighting conditions. This letter presents a perception dataset for bird-scale flapping-wing robots as a tool to help alleviate the aforementioned problems. The presented data include measurements from onboard sensors widely used in aerial robotics and suitable to deal with the perception challenges of flapping-wing robots, such as an event camera, a conventional camera, and two Inertial Measurement Units (IMUs), as well as ground truth measurements from a laser tracker or a motion capture system. A total of 21 datasets of different types of flights were collected in three different scenarios (one indoor and two outdoor). To the best of the authors' knowledge this is the first dataset for flapping-wing robot perception