Abstract:
In theory, an autonomous mobile robot’s ability to navigate with greater intelligence and flexibility in a dynamic environment would be possible if its navigation system was modeled after that of biological creatures. More specifically, to create an agent that mimics neurobiological navigation cells and neural network connections as found in the hippocampus and entorhinal cortex of rodent brains. These navigation cells are the: place cells, head direction cells, boundary cells, and grid cells, as well as memory. To navigate from one waypoint to another, our mobile robot, known as ratbot, uses inspiration from place cells and head direction cells for path integration. This is accomplished through use of vectors and vector mathematics. Additionally, the ratbot uses a field programmable gate array (FPGA) to emulate grid cell functionality for environment mapping and spatial cognition.
