Describing a modular motion system based on a real time process network model
- 23 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 821-827
- https://doi.org/10.1109/iros.1997.655105
Abstract
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 system is decomposed 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 briefly 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 multiprocessor system and it generated desirable actions.Keywords
This publication has 8 references indexed in Scilit:
- SSS: a hybrid architecture applied to robot navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Designing asynchronous parallel process networks for desirable autonomous robot behaviorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Experiences with an architecture for intelligent, reactive agentsJournal of Experimental & Theoretical Artificial Intelligence, 1997
- Vision-based adaptive and interactive behaviors in mechanical animals using the remote-brained approachRobotics and Autonomous Systems, 1996
- A situated view of representation and controlArtificial Intelligence, 1995
- Building brains for bodiesAutonomous Robots, 1994
- A Robot that Walks; Emergent Behaviors from a Carefully Evolved NetworkNeural Computation, 1989
- A robust layered control system for a mobile robotIEEE Journal on Robotics and Automation, 1986