國立虎尾科技大學 |

Reconstructing Insect Pursuit Flight Kinematics in the Wild.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Reconstructing Insect Pursuit Flight Kinematics in the Wild./
作者:	Boddeeti, Haribabu.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	65 p.
附註:	Source: Masters Abstracts International, Volume: 81-02.
Contained By:	Masters Abstracts International81-02.
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13425000
ISBN:	9781085570435

Reconstructing Insect Pursuit Flight Kinematics in the Wild.
Boddeeti, Haribabu.

Reconstructing Insect Pursuit Flight Kinematics in the Wild. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 65 p.

Source: Masters Abstracts International, Volume: 81-02.

Thesis (M.S.)--Northern Illinois University, 2019.

This item is not available from ProQuest Dissertations & Theses.

With their agile maneuvers and aerodynamic feats, flying insects continue to inspire the design, sensing, and control of unmanned aerial vehicles. Among the different behaviors that such insects perform, the mating pursuit stands out in terms of the high speeds and quick turns that each insect performs during the chase. Despite their frequent occurrence in nature, pursuit events between mating insects are rarely analyzed. This is because mating events are difficult to film in the wild or elicit in laboratory settings. The long-term goal of this research is to quantify the kinematics of flying insects in pursuit. The specific objective of this thesis is to apply methods from dynamic estimation and computer vision to develop an automated tracking algorithm for reconstructing three-dimensional flight of insects in the wild.A full-state measurement model that uses epipolar geometry on image optical flow is incorporated into a Kalman filtering algorithm to estimate both three-dimensional position and velocity of a moving target. The tracking approach is validated on a dataset obtained in the laboratory by tracking a rigid body marker in a motion capture facility, where the full-state measurement model reduces the error in speed by more than 70% over the standard partial-state measurement model. The full-state measurement Kalman filtering algorithm is incorporated into a user-assisted tracking system to reconstruct the pursuit kinematics of damselflies filmed in the wild. Image segmentation parameters are optimized on the basis of Hausdorff distance to best isolate individual insects as they fly against a cluttered and moving background. To permit the use of hand-held devices, camera motion is removed automatically by tracking still objects identified using background optical flow. The approach developed in this thesis has the potential to vastly increase the amount of insect pursuit kinematic data that can be used to inspire the sensing and control strategies of micro unmanned aerial vehicles.

ISBN: 9781085570435Subjects--Topical Terms:

557493
Mechanical engineering.
Subjects--Index Terms:

Flying insects

Reconstructing Insect Pursuit Flight Kinematics in the Wild.
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500 $a Source: Masters Abstracts International, Volume: 81-02.
500 $a Advisor: Butail, Sachit.
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506 $a This item is not available from ProQuest Dissertations & Theses.
506 $a This item must not be sold to any third party vendors.
520 $a With their agile maneuvers and aerodynamic feats, flying insects continue to inspire the design, sensing, and control of unmanned aerial vehicles. Among the different behaviors that such insects perform, the mating pursuit stands out in terms of the high speeds and quick turns that each insect performs during the chase. Despite their frequent occurrence in nature, pursuit events between mating insects are rarely analyzed. This is because mating events are difficult to film in the wild or elicit in laboratory settings. The long-term goal of this research is to quantify the kinematics of flying insects in pursuit. The specific objective of this thesis is to apply methods from dynamic estimation and computer vision to develop an automated tracking algorithm for reconstructing three-dimensional flight of insects in the wild.A full-state measurement model that uses epipolar geometry on image optical flow is incorporated into a Kalman filtering algorithm to estimate both three-dimensional position and velocity of a moving target. The tracking approach is validated on a dataset obtained in the laboratory by tracking a rigid body marker in a motion capture facility, where the full-state measurement model reduces the error in speed by more than 70% over the standard partial-state measurement model. The full-state measurement Kalman filtering algorithm is incorporated into a user-assisted tracking system to reconstruct the pursuit kinematics of damselflies filmed in the wild. Image segmentation parameters are optimized on the basis of Hausdorff distance to best isolate individual insects as they fly against a cluttered and moving background. To permit the use of hand-held devices, camera motion is removed automatically by tracking still objects identified using background optical flow. The approach developed in this thesis has the potential to vastly increase the amount of insect pursuit kinematic data that can be used to inspire the sensing and control strategies of micro unmanned aerial vehicles.
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