Title :
A genetic off-line tuner for robotic humanoid visual perception
Author :
Jafari, Shahram ; Jarvis, Ray
Author_Institution :
Intelligent Robotics Res. Centre, Monash Univ., Clayton, Vic., Australia
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.
Keywords :
genetic algorithms; image segmentation; neural nets; real-time systems; robot vision; visual perception; genetic algorithm; genetic offline tuner; neural network; real-time segmentation; robotic humanoid; stereo range finder search area; stereopsis; visual perception; Australia; Cameras; Genetic algorithms; Humanoid robots; Image segmentation; Intelligent robots; Neural networks; Robustness; Tuners; Visual perception;
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
DOI :
10.1109/CEC.2003.1299439