Controlling Biomimetic Underwater Robots With Electronic Nervous Systems

We are developing biomimetic robots based on neurobiological model systems, the lobster and the lamprey. Existing implementations of these robots are based on finite state machine based controllers that instantiate a set of finite state machines based on the organizational units of the animal model nervous systems. These state machines include leg or body axis central pattern generators (CPGs) that generate leg movements or undulations, postural pattern generators that control compensatory appendages and/or adaptive sensors and sensory integration networks that process sensor information. The use of neuron models instead of finite state systems allows one to replicate in great detail the real behavior of the neurobiological system (a network) and, thanks to spiking nature of the models, provides a link between the control functions and the experimental measurements from the animal. The key feature of these models is that because they are based on capturing of nonlinear dynamical behavior of neurons rather than neuronal conductance models, they are simpler, can operate in real time and are thus suitable for robotic control applications.