Evolution of generative design systems for modular physical robots
Recent research has demonstrated the ability for automatic design of the morphology and control of real physical robots using techniques inspired by biological evolution. The main criticism of the evolutionary design approach, however, is that it is doubtful whether it will reach the high complexiti...
Saved in:
Published in | Proceedings - IEEE International Conference on Robotics and Automation Vol. 4; pp. 4146 - 4151 vol.4 |
---|---|
Main Authors | , , |
Format | Conference Proceeding Journal Article |
Language | English |
Published |
IEEE
2001
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Recent research has demonstrated the ability for automatic design of the morphology and control of real physical robots using techniques inspired by biological evolution. The main criticism of the evolutionary design approach, however, is that it is doubtful whether it will reach the high complexities necessary for practical engineering. Here we claim that for automatic design systems to scale in complexity the designs they produce must be made of re-used modules. Our approach is based on the use of a generative design grammar subject to an evolutionary process. Unlike a direct encoding of a design, a generative design specification can re-use components, giving it the ability to create more complex modules from simpler ones. Re-used modules are also valuable for improved efficiency in testing and construction. We describe a system for creating generative specifications capable of hierarchical modularity by combining Lindenmayer systems with evolutionary algorithms. Using this system we demonstrate for the first time a generative system for physical, modular, 2D locomoting robots and their controllers. |
---|---|
Bibliography: | SourceType-Scholarly Journals-2 ObjectType-Feature-2 ObjectType-Conference Paper-1 content type line 23 SourceType-Conference Papers & Proceedings-1 ObjectType-Article-3 |
ISBN: | 0780365763 9780780365766 |
ISSN: | 1050-4729 |
DOI: | 10.1109/ROBOT.2001.933266 |