Recognition of confusing objects for NAO robot

Abstract

Visual processing is one of the most essential tasks in robotics systems. However, it may be affected by many unfavourable factors in the operating environment which lead to imprecisions and uncertainties. Under those circumstances, we propose a multi-camera fusing method applied in a scenario of object recognition for a NAO robot. The cameras capture the same scenes at the same time, then extract feature points from the scene and give their belief about the classes of the detected objects. Dempster’s rule of combination is then used to fuse information from the cameras and provide a better decision. In order to take advantages of heterogeneous sensors fusion, we combine information from 2D and 3D cameras. The results of experiment prove the efficiency of the proposed approach.