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A Method to Produce Minimal Real Time Geometric Representations of Moving Obstacles

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Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 868))

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Abstract

Real time modelling methods are compared for use with a robot manufacturing work-cell and a simple image processing system. The static parts of a robotic manufacturing work-cell are modelled as a number of solid polyhedra. The robot is modelled as a number of connected spheres and cylinders. The static model is renewed when an object enters or leaves the static work-place. Simple polyhedra, spheres and similar 2-D slices in actuator space are compared with other models as representations of objects move in and out of the reach of the robot. Models are compared for their efficiency in accessing data and ability to update as information about moving objects changes. Geometric models of the robot and the robot work-cell are loaded into a path planner to compare the models for efficiency on planning paths around moving objects. Some preliminary results are presented.

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Author information

Authors and Affiliations

  1. School of Engineering, University of Portsmouth, Portsmouth, PO1 3DJ, UK

    David Sanders, Qian Wang, Nils Bausch, Ya Huang, Sergey Khaustov & Ivan Popov

Authors
  1. David Sanders
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  2. Qian Wang
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  3. Nils Bausch
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  4. Ya Huang
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  5. Sergey Khaustov
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  6. Ivan Popov
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Corresponding author

Correspondence to David Sanders .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Sanders, D., Wang, Q., Bausch, N., Huang, Y., Khaustov, S., Popov, I. (2019). A Method to Produce Minimal Real Time Geometric Representations of Moving Obstacles. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_61

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