A novel 1D trifocal tensor-based control for differential-drive robots

This paper presents an image-based approach to perform visual control for differential-drive robots. We use for the first time the elements of the 1D trifocal tensor directly in the control law. The visual control utilizes the usual teach-by showing strategy without requiring any a prior knowledge of the scene and does not need any auxiliary image. The main contribution of the paper is that the proposed two-steps control law ensures total correction of both position and orientation without switching to any other visual constraint rather than the 1D trifocal tensor. The paper exploits the sliding mode control technique in a square system, ensuring stability and robustness for the closed loop. The good performance of the control system is proven via simulations.