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Improving Grasp Performance Using In-Hand Proximity and Contact Sensing

  • Radhen Patel
  • Rebeca Curtis
  • Branden Romero
  • Nikolaus Correll
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 816)

Abstract

We describe the grasping and manipulation strategy that we employed at the autonomous track of the Robotic Grasping and Manipulation Competition at IROS 2016. A salient feature of our architecture is the tight coupling between visual (Asus Xtion) and tactile perception (Robotic Materials), to reduce the uncertainty in sensing and actuation. We demonstrate the importance of tactile sensing and reactive control during the final stages of grasping using a Kinova Robotic arm. The set of tools and algorithms for object grasping presented here have been integrated into the open-source Robot Operating System (ROS). We have focused exclusively on the manipulation aspect (Track 1) of the competition as the bin-picking task (Track 2) would require a different perception strategy, focusing more on object identification.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Radhen Patel
    • 1
  • Rebeca Curtis
    • 1
  • Branden Romero
    • 1
  • Nikolaus Correll
    • 1
  1. 1.University of Colorado BoulderBoulderUSA

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