Improving the performance of the minimum rotational image difference function method using the CMA-ES algorithm in optimal orientation

Orientation is a vital ability for humans and animals. Noticing the way insects orient in nature can be used to improve the orientation skills of robots. The main question of this research can be stated as follows. What kind of information do insects perceive of natural scenes, using their visual ability, that enables them to orient and to find the direction of movement? For orientation, the minimum of rotational image difference function (MrIDF) method can be applied using panoramic image processing [1]. In MrIDF method, even with full shift, if the distance between the location of the current view image and the reference image increases, the return path cannot be correctly identified due to the increase in the difference between the two images. In this paper, we present a solution that can be used to identify the path and return angle in places far from the reference location. We also improve the efficiency the rotIDF minimum method by using the covariance matrix adaptation evolutionary strategy (CMA-ES) optimization algorithm. We show the efficiency of this method via a navigation example. The results show that finding the direction of movement through the proposed algorithm is done with sufficient accuracy and in much less time.