Visual Homing: Surfing on the Epipoles
International Journal of Computer Vision
Solutions and Ambiguities of the Structure and Motion Problem for 1DRetinal Vision
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision - Special issue on image-based servoing
Nonlinear Control Systems
Trilinearity of three perspective views and its associated tensor
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Structure from Motion from Three Affine Views
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
From omnidirectional images to hierarchical localization
Robotics and Autonomous Systems
A novel 1D trifocal tensor-based control for differential-drive robots
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Homography-based visual servo tracking control of a wheeled mobile robot
IEEE Transactions on Robotics
Homography-based visual servo regulation of mobile robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Recursive Camera-Motion Estimation With the Trifocal Tensor
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiple homographies with omnidirectional vision for robot homing
Robotics and Autonomous Systems
Omnidirectional visual control of mobile robots based on the 1D trifocal tensor
Robotics and Autonomous Systems
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We present a new vision-based control approach which drives autonomously a nonholonomic vehicle to a target location. The vision system is a camera fixed on the vehicle and the target location is defined by an image taken previously in that location. The control scheme is based on the trifocal tensor model, which is computed from feature correspondences in calibrated retina across three views: initial, current and target images. The contribution is a trifocal-based control law defined by an exact input-output linearization of the trifocal tensor model. The desired evolution of the system towards the target is directly defined in terms of the trifocal tensor elements by means of sinusoidal functions without needing metric or additional information from the environment. The trifocal tensor presents important advantages for visual control purposes, because it is more robust than two-view geometry as it includes the information of a third view and, contrary to the epipolar geometry, short baseline is not a problem. Simulations show the performance of the approach, which has been tested with image noise and calibration errors.