Designing asynchronous parallel process networks for desirable autonomous robot behaviors

We propose a computational model, BeNet, for describing the brains of autonomous robots and an approach to integrating functions of autonomous robots. BeNet is a network of asynchronously communicating processes that change their state and output vectors and their own frequencies determined by the designer. One can describe a modular system for a desirable behavior as a BeNet that interacts with the real world in real time. We design modules of a BeNet that calculate a part of the internal representation of the brain that is necessary for the desired behavior. The portions of internal representation such as action command, attention command, perceptual/sensational information are realized as messages among the modules. Building such a modular system helps you to develop a brain for a desirable behavior, modifying and extending the described system, since the information flow and the modules´ roles are clear. We have implemented environments for developing BeNet on parallel computers. In these environments, you can describe BeNets that consist of processes of wide range in complexity and frequency of calculation, and test their behavior in the real world immediately. They are effective for building desirable behaviors of autonomous robots. They are demonstated for a ballboy robot, with subsystems for vision, motion and decision