國立虎尾科技大學 |

Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV).

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV)./
作者:	Mangipudi, Chandra Prakash.
面頁冊數:	1 online resource (165 pages)
附註:	Source: Masters Abstracts International, Volume: 55-06.
Contained By:	Masters Abstracts International55-06(E).
標題:	Robotics. -
電子資源:	click for full text (PQDT)
ISBN:	9781369108439

Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV).
Mangipudi, Chandra Prakash.

Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV). - 1 online resource (165 pages)

Source: Masters Abstracts International, Volume: 55-06.

Thesis (M.S.M.E.)

Includes bibliographical references

This thesis details the implementation of a vision aided inertial localization system for a Remotely Operated Vehicle (ROV) in a controlled environment. The vision sub- system features a Raspberry-Pi equipped with the pi-camera and the inertial sub-system consists of an automotive/consumer grade MEMS-IMU operated by an Arduino board (Arduino Due). A novel PnP estimation algorithm, Linear Least Squares - Gradient SO(3) algorithm (SO(3) - PnP), is introduced for pose estimation using the vision sub-system. The position is estimated using a linear least squares approach while the ori- entation is computed iteratively using a gradient descent algorithm. The inertial sensors are used as a dead-reckoning system in between the vision measurements. The cross-talk between the vision and inertial sub-systems is established using ethernet(UDP). Sensor fusion is achieved using Kalman filters. Laboratory experiments validate the accuracy of the Vision-IMU module and enhance the possibility that they can be deployed in an un-controlled ocean environment to compute the pose of the ROV (within a target workspace) w.r.t. a given landmark.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369108439Subjects--Topical Terms:

561941
Robotics.
Index Terms--Genre/Form:

554714
Electronic books.

Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV).
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100 1 $a Mangipudi, Chandra Prakash. $3 1182122
245 1 0 $a Vision Aided Inertial Localization for Remotely Operated Vehicle (ROV).
264 0 $c 2016
300 $a 1 online resource (165 pages)
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337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 55-06.
500 $a Includes supplementary digital materials.
500 $a Adviser: Perry Y. Li.
502 $a Thesis (M.S.M.E.) $c University of Minnesota $d 2016.
504 $a Includes bibliographical references
520 $a This thesis details the implementation of a vision aided inertial localization system for a Remotely Operated Vehicle (ROV) in a controlled environment. The vision sub- system features a Raspberry-Pi equipped with the pi-camera and the inertial sub-system consists of an automotive/consumer grade MEMS-IMU operated by an Arduino board (Arduino Due). A novel PnP estimation algorithm, Linear Least Squares - Gradient SO(3) algorithm (SO(3) - PnP), is introduced for pose estimation using the vision sub-system. The position is estimated using a linear least squares approach while the ori- entation is computed iteratively using a gradient descent algorithm. The inertial sensors are used as a dead-reckoning system in between the vision measurements. The cross-talk between the vision and inertial sub-systems is established using ethernet(UDP). Sensor fusion is achieved using Kalman filters. Laboratory experiments validate the accuracy of the Vision-IMU module and enhance the possibility that they can be deployed in an un-controlled ocean environment to compute the pose of the ROV (within a target workspace) w.r.t. a given landmark.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Robotics. $3 561941
650 4 $a Mechanical engineering. $3 557493
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
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690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Minnesota. $b Mechanical Engineering. $3 845514
773 0 $t Masters Abstracts International $g 55-06(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10155782 $z click for full text (PQDT)