The "fly algorithm" is a fast artificial evolution-based technique devised for the exploration of parameter space in pattern recognition applications. In the application described, we evolve a population which constitutes a particle-based three-dimensional representation of the scene. Each individual represents a three-dimensional point in the scene and may be fitted with optional velocity parameters. Evolution is controlled by a fitness function which contains all pixellevel calculations, and uses classical evolutionary operators (sharing, mutation, crossover). The combined individual approach and low complexity fitness function allow fast processing. Test results and an application to mobile robotics are presented. Keywords Artificial evolution, pattern recognition, computer vision, image processing, parameter space exploration.