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Plane-Based Humanoid Robot Navigation and Object Model Construction for Grasping

  • Pavel Gritsenko
  • Igor Gritsenko
  • Askar Seidakhmet
  • Bogdan KwolekEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11129)

Abstract

In this work we present an approach to humanoid robot navigation and object model construction for grasping using only RGB-D data from an onboard depth sensor. A plane-based representation is used to provide a high-level model of the workspace, to estimate both the global robot pose and pose with respect to the object, and to determine the object pose as well as its dimensions. A visual feedback is used to achieve the desired robot pose for grasping. In the pre–grasping pose the robot determines the object pose as well as its dimensions. In such a local grasping approach, a simulator with our high-level scene representation and a virtual camera is used to fine-tune the motion controllers as well as to simulate and validate the process of grasping. We present experimental results that were obtained in simulations with virtual camera and robot as well as with real humanoid robot equipped with RGB-D camera, which performed object grasping in low-texture layouts.

Keywords

Object grasping Humanoid robot Pose recovery 

Notes

Acknowledgment

This work was supported by Polish National Science Center (NCN) under research grants 2014/15/B/ST6/02808 and 2017/27/B/ST6/01743.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Pavel Gritsenko
    • 2
  • Igor Gritsenko
    • 2
  • Askar Seidakhmet
    • 2
  • Bogdan Kwolek
    • 1
    Email author
  1. 1.AGH University of Science and TechnologyKrakowPoland
  2. 2.Al-Farabi Kazakh National UniversityAlmatyKazakhstan

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