BeNet: A Parallel Process Model for Describing Autonomous Robot Brain.

Abstract

It is difficult to design a brain of an autonomous robot. The designer must describe a system that interacts with the dynmaic physical world through sensors and motors. In order to design a desirable behavior, it is necessary to combine a set of modules that interact with each other and with the external world. In this paper, we propose an abstract model for describing such a system, BeNet, a network of processes that change their state asynchronously and periodically. The designer describes modules that interact with the other modules and the environment in parallel, by programming rules for changing the output and internal state and by determining their cycles. Designing on BeNet, you can describe a system completely which interacts with the environment in real time, and in which the role of each module and the flow of information are clear, in a simple manner. We implemented programming environments, BNRB's that enable the designer to program and actualize BeNets for autonomous robots. We discuss on the advantages of our approach to designing a robot brain as a BeNet, showing how to realize brains for desirable autonomous behaviors by integrating parallel modules for perception, motion and decision.