A genetic off-line tuner for robotic humanoid visual perception

Abstract

Here, a robust tuner is presented that has been developed for support of early visual understanding by a robotic humanoid, sg1, under development. One of the achieved goals is to speed up the process of real-time segmentation by eliminating any tuning sessions from the online process and carrying them out offline. Effectiveness values (credits) assigned to stereo-based range findings and colour components (red, green, blue) are some of the tuned parameters. However, more than nine parameters (such as: stereo range finder search area, minimum and maximum size of regions, thresholds...) are tuned using a genetic algorithm. A novel idea for automatic evaluation of the region-edge segmentation has been applied as well.