Vision-based Navigation and Manipulation

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Indoor Navigation


  • As a map representation, we proposed a hybrid map using object-spatial layout-route information.
  • Our global localization is based on object recognition and its pose relationship, and the local localization uses 2D-contour matching by 2D laser scanning data.
  • Our map representation is like this:

  • The Object-based global localization is as follows:

Related papers

  • S Park, Sung-Kee Park, "Global localization for mobile robots using reference scan matching," International Journal of Control, Automation and Systems 12 (1), 156-168, 2014.
  • S Kim, H Cheong, DH Kim, Sung-Kee Park, "Context-based object recognition for door detection," Advanced Robotics (ICAR), 2011 15th International Conference on, 155-160, 2011.
  • S Park, Sung-Kee Park, "pectral scan matching and its application to global localization for mobile robots," Robotics and Automation (ICRA), 2010 IEEE International Conference on, 1361-1366. 2010.
  • S Park, S Kim, M Park, Sung-Kee Park, "Vision-based global localization for mobile robots with hybrid maps of objects and spatial layouts," Information Sciences 179 (24), 4174-4198, 2009.

Unknown Objects Grasping


  • With a stereo vision(passive 3D sensor) and a Jaw-type hand, we studied a method for any unknown object grasping.
  • In the context of perception with only one-shot 3D image, three graspable directions such as lift-up, side and frontal direction are suggested, and an affordance-based grasp, handle graspable, is also proposed.
  • Our experimental movie clip :
  • Our grasp directions are as follows:
Grasp directions.jpg

  • The schema of our whole grasping process is like this:

Related papers

  • RK Ala, DH Kim, SY Shin, CH Kim, Sung-Kee Park, A 3D-grasp synthesis algorithm to grasp unknown objects based on graspable boundary and convex segments," Information Sciences 295, 91-106, 2015