Describing a modular motion system based on a real time process network model

The brain of an autonomous robot generates signals to the motors in each situation of the dynamical real world to achieve various tasks. The designer of it has to describe a complex system that maps the sensation and the mental state of the robot into the commands to the motors. In this paper, we present an approach to realizing a complex motion system by describing an asynchronous network of real time computational modules that represent dynamical systems with input, output and internal state completely. In our approach, the designer decomposes the system into parallel modules that calculate their assigned parts of the internal state at regular intervals. We stipulate the roles of the modules so that we can design each module independently and modify or extend the system easily. We have developed programming environments in which we can describe each module and the network brie BLOCKINy in programming languages and test it immediately in the real world. We describe how to design an understandable hierarchical network for desirable actions of an autonomous legged robot. The system has modules that run in parallel for generating motion patterns and actions. The described network was simulated in real time on a multi-processor system and it generated desirable actions.