Agile Autonomy: Learning High-Speed Vision-Based Flight

Author:   Antonio Loquercio
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   153
ISBN:  

9783031272875


Pages:   55
Publication Date:   30 April 2024
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Agile Autonomy: Learning High-Speed Vision-Based Flight


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Author:   Antonio Loquercio
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   153
Weight:   0.303kg
ISBN:  

9783031272875


ISBN 10:   3031272870
Pages:   55
Publication Date:   30 April 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1: Introduction.- 2: Contribution.- 3: Future Directions.

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Author Information

Antonio Loquercio is a robotics scientist and engineer originally from Naples, Italy. He is a recipient of the ETH Medal for outstanding master thesis and the Georges Giralt Ph.D. award, the most prestigious prize for a European dissertation in robotics. He is known for his research on high-performance agile robotics, particularly for drones and legged robots. Growing up in the countryside near Rome, he was always fascinated by the wonders of nature. The desire to understand and recreate such wonders motivated him to embark on a career in robotics. He was an undergraduate at the University of Rome, Tor Vergata, where he studied mechanical and electrical engineering. Afterward, he moved to Zurich, Switzerland, where he was first a master's and then a graduate student at the Swiss Federal Institute of Technology (ETH) and the University of Zurich. He is currently a postdoctoral scholar at the University of California, Berkeley. He has contributed more than 20 scientific papers in robotics and computer vision. His works were awarded several recognitions, including the best system paper award at the conference on robot learning, the best paper award honorable mention at the conference Robotics: Science and Systems, and the Transaction on Robotics Best Paper Award honorable mention. 

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