Visual object recognition for robot tasks in real-life scenarios

On the way to autonomous robotic systems, key issues are object detection and recognition. In this paper, we aim at robustly detecting and recognizing different objects in real-life scenarios from a visual input when robot manipulation is the goal task. For that, and based on the human vision system performance, the system computes object´s colour, motion and shape cues and combines them in a probabilistic manner to accurately achieve object identification and recognition task. More-over, a Graphical Processing Unit (GPU) is used to fulfill the requirement for real-time visual data processing. In addition, it has been implemented and tested on a robotic platform.