東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Learning to Soar Using Atmospheric T...

Nallamala, Gautam Reddy.

FindBook

Google Book

Amazon

博客來

Learning to Soar Using Atmospheric Thermals.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Learning to Soar Using Atmospheric Thermals./
作者:	Nallamala, Gautam Reddy.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	88 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
Contained By:	Dissertations Abstracts International81-03B.
標題:	Biophysics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13883926
ISBN:	9781085642422

Learning to Soar Using Atmospheric Thermals.
Nallamala, Gautam Reddy.

Learning to Soar Using Atmospheric Thermals. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 88 p.

Source: Dissertations Abstracts International, Volume: 81-03, Section: B.

Thesis (Ph.D.)--University of California, San Diego, 2019.

This item must not be sold to any third party vendors.

Soaring birds often rely on ascending thermal plumes (thermals) in the atmosphere as they search for prey or migrate across large distances. How soaring birds find and navigate thermals is unknown. This is a scenario where experiments are difficult to control and the strategies used by birds are difficult to infer. In this work, I used modern methods from artificial intelligence as tools to generate hypotheses for the strategies and mechanosensory cues that birds may use in order to soar effectively.In Chapter 1, I describe how a technique from artificial intelligence, namely, reinforcement learning, is used to train virtual gliders with bird-like aerodynamic properties to navigate simulated convective turbulent flows. By experimenting with the learning environment, we find that gliders need to sense and respond to two cues in order to soaring effectively: the vertical wind acceleration and the velocity differences across the wings. The learning process also yields a strategy for soaring within thermals that relies on these two cues.In Chapter 2, I describe the details of how lessons from the simulations were used to teach gliders to navigate atmospheric thermals in the field. Gliders of two-meter wingspan were equipped with a flight controller that precisely controlled the bank angle and pitch, modulating these at intervals with the aim of gaining as much lift as possible. A navigational strategy was determined solely from the gliders pooled experiences collected over several days in the field. The strategy relies on methods to accurately estimate the local vertical wind accelerations and the roll-wise torques on the glider, which serve as navigational cues. I show that vertical wind accelerations and roll-wise torques are effective mechanosensory cues for soaring and provide a navigational strategy applicable to autonomous soaring vehicles.

ISBN: 9781085642422Subjects--Topical Terms:

518360
Biophysics.
Subjects--Index Terms:

Animal behavior

Learning to Soar Using Atmospheric Thermals.
LDR:03056nmm a2200397 4500 001 2265880
005 20200529130308.5
008 220629s2019 ||||||||||||||||| ||eng d
020 $a 9781085642422
035 $a (MiAaPQ)AAI13883926
035 $a AAI13883926
040 $a MiAaPQ $c MiAaPQ
100 1 $a Nallamala, Gautam Reddy. $3 3543060
245 1 0 $a Learning to Soar Using Atmospheric Thermals.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 88 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
500 $a Advisor: Vergassola, Massimo.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Soaring birds often rely on ascending thermal plumes (thermals) in the atmosphere as they search for prey or migrate across large distances. How soaring birds find and navigate thermals is unknown. This is a scenario where experiments are difficult to control and the strategies used by birds are difficult to infer. In this work, I used modern methods from artificial intelligence as tools to generate hypotheses for the strategies and mechanosensory cues that birds may use in order to soar effectively.In Chapter 1, I describe how a technique from artificial intelligence, namely, reinforcement learning, is used to train virtual gliders with bird-like aerodynamic properties to navigate simulated convective turbulent flows. By experimenting with the learning environment, we find that gliders need to sense and respond to two cues in order to soaring effectively: the vertical wind acceleration and the velocity differences across the wings. The learning process also yields a strategy for soaring within thermals that relies on these two cues.In Chapter 2, I describe the details of how lessons from the simulations were used to teach gliders to navigate atmospheric thermals in the field. Gliders of two-meter wingspan were equipped with a flight controller that precisely controlled the bank angle and pitch, modulating these at intervals with the aim of gaining as much lift as possible. A navigational strategy was determined solely from the gliders pooled experiences collected over several days in the field. The strategy relies on methods to accurately estimate the local vertical wind accelerations and the roll-wise torques on the glider, which serve as navigational cues. I show that vertical wind accelerations and roll-wise torques are effective mechanosensory cues for soaring and provide a navigational strategy applicable to autonomous soaring vehicles.
590 $a School code: 0033.
650 4 $a Biophysics. $3 518360
650 4 $a Aerospace engineering. $3 1002622
650 4 $a Computer science. $3 523869
650 4 $a Behavioral sciences. $3 529833
650 4 $a Artificial intelligence. $3 516317
650 4 $a Robotics. $3 519753
653 $a Animal behavior
653 $a Autonomous glider
653 $a Reinforcement learning
653 $a Thermal soaring
690 $a 0786
690 $a 0538
690 $a 0984
690 $a 0800
690 $a 0602
690 $a 0771
710 2 $a University of California, San Diego. $b Physics. $3 1035951
773 0 $t Dissertations Abstracts International $g 81-03B.
790 $a 0033
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13883926