Evolving neural networks for the control of a lenticular blimp

Authors:
Stéphane Doncieux;Jean-Arcady Meyer
Affiliations:
AnimatLab - LIP6, France;AnimatLab - LIP6, France
Venue:
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Year:
2003

Citing 3
Cited 2

Evolutionary Robotics: The Biology,Intelligence,and Technology

Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolving Vision-Based Flying Robots

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Evolutionary approaches to neural control of rolling, walking, swimming and flying animats or robots

Biologically inspired robot behavior engineering

Incremental evolution of target-following neuro-controllers for flapping-wing animats

SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Encouraging behavioral diversity in evolutionary robotics: An empirical study

Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

We used evolution to shape a neural controller for keeping a blimp at a given altitude, and as horizontal as possible, despite disturbing winds. The blimp has a lenticular shape whose aerodynamic properties make it quite different from a classical cigar-shaped airship. Evolution has exploited these features to generate a neural network that proved to be more efficient than a hand-designed PID-based controller that independently controlled the blimp's three degrees of freedom.