Gait coordination of hexapod walking robots using mutual-coupled immune networks

Biological information processing systems are amongst the ultimate decentralized systems, and are expected to provide various fruitful ideas for engineering fields, especially robotics. Among these systems, the brain-nervous system and genetic system have already been widely used by modeling as neural networks and genetic algorithms, respectively. The immune system also plays an important role in coping with a dynamically changing environment by constructing self-nonself recognition networks among different species of antibodies. This system also has a lot of interesting features such as learning, self-organizing abilities and so on viewed from the engineering standpoint. However, the immune system has not yet been applied to engineering fields. We propose a new hypothesis concerning the structure of the immune system, called the mutual-coupled immune network hypothesis, based on recent studies on immunology. We apply this idea to gait acquisition of a hexapod walking robot as a practical example. Finally, the feasibility of our proposed method is confirmed by simulations.