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Uncalibrated robotic visual servo tr...

Munnae, Jomkwun.

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Uncalibrated robotic visual servo tracking for large residual problems.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Uncalibrated robotic visual servo tracking for large residual problems./
作者:	Munnae, Jomkwun.
面頁冊數:	327 p.
附註:	Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
Contained By:	Dissertation Abstracts International72-06B.
標題:	Engineering, Mechanical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3451272
ISBN:	9781124564210

Uncalibrated robotic visual servo tracking for large residual problems.
Munnae, Jomkwun.

Uncalibrated robotic visual servo tracking for large residual problems. - 327 p.

Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .

Thesis (Ph.D.)--Georgia Institute of Technology, 2010.

In visually guided control of a robot, a large residual problem occurs when the robot configuration theta is not in the neighborhood of the target acquisition configuration theta*. Most existing uncalibrated visual servoing algorithms use quasi-Gauss-Newton methods which are effective for small residual problems. The solution used in this study switches between a full quasi-Newton method for large residual case and the quasi-Gauss-Newton methods for the small case. Visual servoing to handle large residual problems for tracking a moving target has not previously appeared in the literature.

ISBN: 9781124564210Subjects--Topical Terms:

783786
Engineering, Mechanical.

Uncalibrated robotic visual servo tracking for large residual problems.
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245 1 0 $a Uncalibrated robotic visual servo tracking for large residual problems.
300 $a 327 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
500 $a Adviser: Harvey Lipkin.
502 $a Thesis (Ph.D.)--Georgia Institute of Technology, 2010.
520 $a In visually guided control of a robot, a large residual problem occurs when the robot configuration theta is not in the neighborhood of the target acquisition configuration theta*. Most existing uncalibrated visual servoing algorithms use quasi-Gauss-Newton methods which are effective for small residual problems. The solution used in this study switches between a full quasi-Newton method for large residual case and the quasi-Gauss-Newton methods for the small case. Visual servoing to handle large residual problems for tracking a moving target has not previously appeared in the literature.
520 $a For large residual problems various Hessian approximations are introduced including an approximation of the entire Hessian matrix, the dynamic BFGS (DBFGS) algorithm, and two distinct approximations of the residual term, the modified BFGS (MBFGS) algorithm and the dynamic full Newton method with BFGS ( DFN-BFGS) algorithm. Due to the fact that the quasi-Gauss-Newton method has the advantage of fast convergence, the quasi-Gauss-Newton step is used as the iteration is sufficiently near the desired solution. A switching algorithm combines a full quasi-Newton method and a quasi-Gauss-Newton method. Switching occurs if the image error norm is less than the switching criterion, which is heuristically selected.
520 $a An adaptive forgetting factor called the dynamic adaptive forgetting factor (DAFF) is presented. The DAFF method is a heuristic scheme to determine the forgetting factor value based on the image error norm. Compared to other existing adaptive forgetting factor schemes, the DAFF method yields the best performance for both convergence time and the RMS error.
520 $a Simulation results verify validity of the proposed switching algorithms with the DAFF method for large residual problems. The switching MBFGS algorithm with the DAFF method significantly improves tracking performance in the presence of noise. This work is the first successfully developed model independent, vision-guided control for large residual with capability to stably track a moving target with a robot.
590 $a School code: 0078.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, Robotics. $3 1018454
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710 2 $a Georgia Institute of Technology. $3 696730
773 0 $t Dissertation Abstracts International $g 72-06B.
790 1 0 $a Lipkin, Harvey, $e advisor
790 $a 0078
791 $a Ph.D.
792 $a 2010
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