Anytime coevolution of form and function

Author

Bugajska, Magdalena D. ; Schultz, Alan C.

Author_Institution

Navy Center for Appl. Res. in Artificial Intelligence, Naval Res. Lab., Washington, DC, USA

Volume

1

fYear

2003

fDate

8-12 Dec. 2003

Firstpage

359

Abstract

This paper describes an approach to continuous coevolution of form (the morphology) and function (the control behaviour) for autonomous vehicles. This study focuses on coevolution of the characteristics such as beam width and range of individual sensors in the sensor suite, and the reactive strategies for collision-free navigation for an autonomous micro air vehicle. The results of the evolution of the system in a fixed simulation model were compared to case-based anytime learning (also called continuous and embedded learning) where the simulation model was updated over time to better match changes in the environment.

Keywords

collision avoidance; mobile robots; navigation; sensors; anytime coevolution; autonomous micro air vehicle; autonomous vehicles; beam width; case-based anytime learning; collision-free navigation; continuous coevolution; continuous learning; control behaviour; embedded learning; fixed simulation model; form coevolution; function coevolution; individual sensors; morphology; reactive strategies; sensor suite; Algorithm design and analysis; Automatic control; Control systems; Mobile robots; Morphology; Navigation; Remotely operated vehicles; Robotics and automation; Sensor phenomena and characterization; Vehicle safety;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2003. CEC '03. The 2003 Congress on

Print_ISBN

0-7803-7804-0

Type

conf

DOI

10.1109/CEC.2003.1299598

Filename

1299598