Visual object recognition for robot tasks in real-life scenarios

Abstract

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.