Scene Perception and Recognition in Industrial Environments for Human-Robot Interaction

  • Nikhil Somani
  • Emmanuel Dean-León
  • Caixia Cai
  • Alois Knoll
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8033)


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.


Point Cloud Object Recognition Perception Module Partial View Scene Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nikhil Somani
    • 1
  • Emmanuel Dean-León
    • 2
  • Caixia Cai
    • 1
  • Alois Knoll
    • 1
  1. 1.Fakultät für InformatikTechnische Universität MünchenGarching bei MünchenGermany
  2. 2.Cyber-Physical Systemsfortiss - An-Institut der Technischen Universität MünchenMünchenGermany

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