Towards Reliable Grasping and Manipulation in Household Environments

  • Matei CiocarlieEmail author
  • Kaijen Hsiao
  • Edward Gil Jones
  • Sachin Chitta
  • Radu Bogdan Rusu
  • Ioan A. Şucan
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 79)


We present a complete software architecture for reliable grasping of household objects. Our work combines aspects such as scene interpretation from 3D range data, grasp planning, motion planning, and grasp failure identification and recovery using tactile sensors. We build upon, and add several new contributions to the significant prior work in these areas. A salient feature of our work is the tight coupling between perception (both visual and tactile) and manipulation, aiming to address the uncertainty due to sensor and execution errors. This integration effort has revealed new challenges, some of which can be addressed through system and software engineering, and some of which present opportunities for future research. Our approach is aimed at typical indoor environments, and is validated by long running experiments where the PR2 robotic platform was able to consistently grasp a large variety of known and unknown objects. The set of tools and algorithms for object grasping presented here have been integrated into the open-source Robot Operating System (ROS).


Point Cloud Motion Planning Unknown Object Robot Operating System Grasp Planning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2014

Authors and Affiliations

  • Matei Ciocarlie
    • 1
    Email author
  • Kaijen Hsiao
    • 1
  • Edward Gil Jones
    • 1
  • Sachin Chitta
    • 1
  • Radu Bogdan Rusu
    • 1
  • Ioan A. Şucan
    • 2
  1. 1.Willow Garage Inc.Menlo ParkUSA
  2. 2.Rice UniversityHoustonUSA

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