3-D Modeling for Robotic Tactile Object Recognition

  • Peter K. Allen


Solid modeling techniques have proven quite successful in the design and synthesis of objects for manufacturing. However, solid modeling techniques have proven less successful in object recognition tasks. The creation of a CAD based robotics cell requires the ability to perform shape recognition from a variety of sensor sources, including vision, touch and ranging. Superquadric models have been used successfully in visual recognition tasks, and they appear to possess a number of important attributes for robotic tactile object recognition tasks that need to derive shape from sparse tactile sensor data. Superquadrics can be used to model many complex shapes, including arbitrary taperings and bendings, within a relatively small and stable Refsmeter space. This paper discusses the components of such a model and its relationship to active tactile sensing strategies with a multi-fingered robotic hand.


Object Recognition Tactile Sensor Haptic Perception Object Recognition Task Object Recognition System 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Peter K. Allen
    • 1
  1. 1.Department of Computer ScienceColumbia UniversityNew YorkUSA

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