Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
A novel 1D trifocal tensor-based control for differential-drive robots
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Image-Based Visual Servoing for Nonholonomic Mobile Robots Using Epipolar Geometry
IEEE Transactions on Robotics
Localization and Matching Using the Planar Trifocal Tensor With Bearing-Only Data
IEEE Transactions on Robotics
Recursive Camera-Motion Estimation With the Trifocal Tensor
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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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.