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Model-Based Stereo-Tracking of Non-Polyhedral Objects for Automatic Disassembly Experiments

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Abstract

Automatic disassembly tasks in the engine compartment of a used car constitute a challenge for control of a disassembly robot by machine vision. Experience in exploratory experiments under such conditions forced us to abandon data-driven aggregation of edge elements into straight-line data segments in favor of a direct association of individual edge elements with model segments obtained from scene domain models of tools and workpieces. In addition, we had to switch from a conventional single camera hand-eye configuration to a movable stereo-configuration mounted on a separate ‘observer’ robot. A generalisation of our model-based tracking includes the parameters, which characterize the relative pose of one camera with respect to the other one of the stereo-camera set-up, into the set of parameters to be re-estimated for each new stereo image pair. This results in a continuous re-calibration during a relative movement between stereo-camera set-up and tracked objects. Our approach had to be extended further in order to cope with non-polyhedral objects.

The methodological improvements of machine vision in the course of this research are treated in detail. We discuss, moreover, the systematic trading-off of computational resources for increased robustness which is vital for visual control of automatic disassembly robots.

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Authors and Affiliations

  1. Institut für Algorithmen und Kognitive Systeme, Universität Karlsruhe (TH), Postfach 6980, 76128, Karlsruhe, Germany

    Martin Tonko & Hans-Hellmut Nagel

  2. Fraunhofer-Institut für Informations- und Datenverarbeitung IITB, Fraunhoferstraβe 1, 76131, Karlsruhe, Germany

    Hans-Hellmut Nagel

Authors
  1. Martin Tonko
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  2. Hans-Hellmut Nagel
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Tonko, M., Nagel, HH. Model-Based Stereo-Tracking of Non-Polyhedral Objects for Automatic Disassembly Experiments. International Journal of Computer Vision 37, 99–118 (2000). https://doi.org/10.1023/A:1008133614366

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