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Applications of Robot Grasping Simulation

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Part of the book series: Cognitive Systems Monographs ((COSMOS,volume 19))

Abstract

We developed the OpenGRASP framework, presented in the previous chapter, as part of the work of the GRASP project. Within the project the toolkit was used as the main tool for reasoning and prediction of object properties as well as task constraints of manipulation and grasping activities executed by robots. In this chapter, these applications of the simulator in robot grasping are presented. It is demonstrated how grasp simulation is a key tool for constructing a world model and understanding the robot’s environment. Additionally, we demonstrate how to achieve a complete dynamic simulation of a humanoid robot using the developed toolkit.

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Notes

  1. 1.

    Vision4Robotics Group, Automation and Control Institute, Vienna University of Technology, Vienna, Austria.

  2. 2.

    Robotic Intelligence Lab, Universitat Jaume I, Castellon, Spain.

  3. 3.

    Autonomous Motion Lab, MPI for Intelligent Systems, Germany.

  4. 4.

    Robotic Intelligence Lab, Universitat Jaume I, Castellon, Spain.

  5. 5.

    Computer Vision and Active Perception lab, KTH, Sweden.

  6. 6.

    The ground truth object models were obtained from http://i61p109.ira.uka.de/ObjectModelsWebUI/.

  7. 7.

    http://opencv.willowgarage.com

  8. 8.

    A video of the experiment can be found at http://youtu.be/jskDy2IfQr4.

  9. 9.

    Computer Vision and Active Perception lab, KTH, SE.

  10. 10.

    Robotic Intelligence Laboratory, UJI, ES.

  11. 11.

    Humanoids and Intelligence Systems Lab, Institute for Anthropomatics, KIT, DE.

  12. 12.

    Automation and Control Institute, TUW, AT.

  13. 13.

    Robotic Intelligence Lab, Universitat Jaume I, Castellon, Spain.

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Correspondence to Beatriz León .

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León, B., Morales, A., Sancho-Bru, J. (2014). Applications of Robot Grasping Simulation. In: From Robot to Human Grasping Simulation. Cognitive Systems Monographs, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-01833-1_4

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  • DOI: https://doi.org/10.1007/978-3-319-01833-1_4

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