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GPU-based Power-Grasp And Placement Planners For Unknown Environments
Johannes Baumgartl , Dominik Henrich

Abstract (deutsch)
A Personal Robot should be able to handle unknown objects in unknown environments. For a manipulation task the question of what to do with an object once it has been grasped, is one of the most essential ones besides the grasping task itself. Moreover, the planning time should be at least as fast as the time the robot needs for its grasping/placing motions. We propose a combination of a fast grasp and placement planner that deals with sensor-modelled objects. They share novel pose computation steps that reduce the amount of computational intensive collision tests. By means of experiments we evaluate the computation time for the pose computation. Furthermore, we present the qualitative results of experiments showing accurate grasps and object placements.

Publication data

Year: 2014
Publication date: 03. June 2014
Place: Munich
Source: Joint 45th International Symposium on Robotics - ISR 2014 and 8th GERMAN Conference on Robotics - ROBOTIK 2014
Project: PAP
Keywords (deutsch): Robotik
Keywords (english): industrial robots , manipulation skills , on-line algorithms , parallel processing
Referrer: http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=baumgartl2014b

BibTeX

@ARTICLE{baumgartl2014b,
  TITLE             = "GPU-based Power-Grasp And Placement Planners For Unknown Environments",
  AUTHOR            = "Baumgartl, Johannes and Henrich, Dominik",
  YEAR              = "2014",
  JOURNAL           = "Joint 45th International Symposium on Robotics - ISR 2014 and 8th GERMAN Conference on Robotics - ROBOTIK 2014",
  HOWPUBLISHED      = "\url{http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=baumgartl2014b}",
}

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baumgartl2014b.GPUbased.PowerGrasp.And.Placement.Planners.For.Unknown.Environments.pdf   2.1M   english   PDF   download preprint


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