DocumentCode :
2689016
Title :
Pose-estimation-based visual servoing for differential-drive robots using the 1D trifocal tensor
Author :
Becerra, H.M. ; Sagues, C.
Author_Institution :
DIIS-I33A, Univ. de Zaragoza, Zaragoza, Spain
fYear :
2009
fDate :
10-15 Oct. 2009
Firstpage :
5942
Lastpage :
5947
Abstract :
A pose-estimation-based approach to perform visual control for differential-drive robots is presented in this paper. Our scheme recovers the camera location (position and orientation) using an extended kalman filter (EKF) algorithm with the 1D trifocal tensor (TT) as measurement model. This new visual servoing scheme allows knowing the real world path performed by the robot without the computational load introduced by position-based approaches. A state-estimated feedback control law is designed to solve a tracking problem for the lateral and longitudinal robot coordinates. The desired trajectories to be tracked ensure total correction of both position and orientation using a single control law, even though the orientation is a DOF in the control system. The effectiveness of our approach is tested via simulations.
Keywords :
Kalman filters; feedback; mobile robots; pose estimation; state estimation; tensors; visual servoing; 1D trifocal tensor; camera location; differential-drive robots; extended Kalman filter algorithm; lateral robot coordinates; longitudinal robot coordinates; pose-estimation; single control law; state-estimated feedback control law; visual control; visual servoing; Cameras; Control systems; Feedback control; Position measurement; Robot control; Robot kinematics; Robot vision systems; Tensile stress; Trajectory; Visual servoing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
Type :
conf
DOI :
10.1109/IROS.2009.5354658
Filename :
5354658
Link To Document :
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