Optimization of the POSIT algorithm for indoor autonomous navigation

This paper presents an optimization of POSIT (Pose from Orthographic and Scaling with Iterations), a model-based camera location algorithm, in the domain of indoor mobile robot navigation. The method finds the rotation matrix and the translation vector of the camera with respect to an object. The novelty of the proposed modified algorithm is that it does not need the perfect knowledge of camera parameters. A new definition of the scaling factor has been introduced in the scaled orthographic projection. Due to the peculiarity of the indoor bounded workspace a new formulation of the translation vector has been used. The new method has been successfully applied in a real environment considering a goal-directed navigation task for our real robot Khepera. The experimentation has shown better results in comparison with the original POSIT algorithm.