Agile Autonomy: Learning High-Speed Vision-Based Flight [electronic resource] / by Antonio Loquercio.

Por: Loquercio, Antonio [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries Springer Tracts in Advanced Robotics ; 153Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: XX, 55 p. 34 illus., 32 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031272882Tema(s): Robotics | Computational intelligence | Aerospace engineering | Astronautics | Robotics | Computational Intelligence | Aerospace Technology and AstronauticsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 629.892 Clasificación LoC:TJ210.2-211.495Recursos en línea: Libro electrónicoTexto
Contenidos:
1: Introduction -- 2: Contribution -- 3: Future Directions.
En: Springer Nature eBookResumen: This book presents the astonishing potential of deep sensorimotor policies for agile vision-based quadrotor flight. Quadrotors are among the most agile and dynamic machines ever created. However, developing fully autonomous quadrotors that can approach or even outperform the agility of birds or human drone pilots with only onboard sensing and computing is challenging and still unsolved. Deep sensorimotor policies, generally trained in simulation, enable autonomous quadrotors to fly faster and more agile than what was possible before. While humans and birds still have the advantage over drones, the author shows the current research gaps and discusses possible future solutions.
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1: Introduction -- 2: Contribution -- 3: Future Directions.

This book presents the astonishing potential of deep sensorimotor policies for agile vision-based quadrotor flight. Quadrotors are among the most agile and dynamic machines ever created. However, developing fully autonomous quadrotors that can approach or even outperform the agility of birds or human drone pilots with only onboard sensing and computing is challenging and still unsolved. Deep sensorimotor policies, generally trained in simulation, enable autonomous quadrotors to fly faster and more agile than what was possible before. While humans and birds still have the advantage over drones, the author shows the current research gaps and discusses possible future solutions.

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