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Record Nr. |
UNINA9910717421003321 |
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Autore |
Loquercio Antonio |
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Titolo |
Agile autonomy : learning high-speed vision-based flight / / Antonio Loquercio |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2023] |
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©2023 |
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ISBN |
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9783031272882 |
9783031272875 |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (69 pages) |
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Collana |
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Springer Tracts in Advanced Robotics, , 1610-742X ; ; 153 |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1: Introduction -- 2: Contribution -- 3: Future Directions. |
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Sommario/riassunto |
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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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