Scene perception and recognition in industrial environments for human-robot interaction

Abstract

In this paper, a scene perception and recognition module aimed at use in typical industrial scenarios is presented. The major contribution of this work lies in a 3D object detection, recognition and pose estimation module, which can be trained using CAD models and works for noisy data, partial views and in cluttered scenes. This algorithm was qualitatively and quantitatively compared with other state-of-art algorithms. Scene perception and recognition is an important aspect in the design of intelligent robotic systems which can adapt to unstructured and rapidly changing environments. This work has been used and evaluated in several experiments and demonstration scenarios for autonomous process plan execution, human-robot interaction and co-operation. © 2013 Springer-Verlag.