Robustness study of a multimodal compass inspired from hd-cells and dynamic neural fields

Abstract

In this paper, we study a robust multi modal compass for a vision based navigation system. The model mimics several aspects of the head direction cells found in the postsubiculum of the rat. Idiothetic information is recalibrated according to the learning of visual stimuli associated to robust landmarks. The model is based on dynamic neural fields allowing building attractors associated to the compass direction. The novelty of the model relies in the way the decision of the sensor fusion is re-injected in the visual compass allowing a robust decision-making. Robotics experiments show the capability of the model to merge different sources of information when their predictions are coherent. When the information become incoherent because the inputs propose quite different directions, the system is able to bifurcate on one coherent solution in order to maintain the temporal coherency of its behavior. © 2014 Springer International Publishing Switzerland.