Agile Autonomy: Learning High-Speed Vision-Based Flight
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Beschreibung
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.
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.
Shows algorithms to operationalize vision-based high-speed flight of drones in unstructured environments Exploits the synergy between perception and action which characterizes natural and artificial agents alike Winner of the George Giralt PhD award for extraordinary contributions in Robotics
Autor*in
Antonio Loquercio
Themen in »Agile Autonomy: Learning High-Speed Vision-Based Flight«
Robotics Drones Machine Learning Vision-Based Flight Autonomous Systems