A hardwired polymorphic neural network for a CPU-less autonomous mobile robot

In order to construct truly autonomous mobile robots, the concept of implementability is highly indispensable: all parts such as controllers, power systems, batteries should be embedded inside a body. Therefore, the implementing controller on hardware is one of the most promising ways, since this contributes to low power consumption and miniaturization and so on. Another crucial requirement in the field of autonomous mobile robots is robustness. That is, autonomous mobile robots have to cope with their unpredictably changing environment in real time. In this study, to meet these requirements the concept of dynamically rearrangeable electrical circuit (DREC) is proposed and we implement this onto FPGAs as physical electronic circuits by borrowing the idea from neuromodulation widely observed in biological nervous systems by the diffusion-reaction mechanism of neuromodulators. We developed the DREC for the peg-pushing task as a practical example. We confirmed that the physical DREC can successfully regulate the behavior according to the situation by changing its properties in real time.