Transition cells and neural fields for navigation and planning

We have developped a mobile robot control system based on hippocampus and prefrontal models. We propose an alternative to models that rely on cognitive maps linking place cells. Our experiments show that using transition cells is more efficient than using place cells. The transition cell links two locations with the integrated direction used. Furthermore, it is possible to fuse the different directions proposed by nearby transitions and obstacles into an effective direction by using a Neural Field. The direction to follow is the stable fixed point of the Neural Field dynamics, and its derivative gives the angular rotation speed. Simulations and robotics experiments are carried out.