Agile Autonomy: Learning High-Speed Vision-Based Flight

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 huma...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Kaituhi matua: Loquercio, Antonio (Author)
Kaituhi rangatōpū: SpringerLink (Online service)
Hōputu: Tāhiko īPukapuka
Reo:Ingarihi
I whakaputaina: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Putanga:1st ed. 2023.
Rangatū:Springer Tracts in Advanced Robotics, 153
Ngā marau:
Urunga tuihono:https://doi.org/10.1007/978-3-031-27288-2
Ngā Tūtohu: Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

MARC

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520 |a 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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