Guided pushing for object singulation

Tucker Hermans, James M. Rehg, Aaron Bobick

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We propose a novel method for a robot to separate and segment objects in a cluttered tabletop environment. The method leverages the fact that external object boundaries produce visible edges within an object cluster. We achieve this singulation of objects by using the robot arm to perform pushing actions specifically selected to test whether particular visible edges correspond to object boundaries. We verify the separation of objects after a push by examining the clusters formed by geometric segmentation of regions residing on the table surface. To avoid explicitly representing and tracking edges across push behaviors we aggregate over all edges in a given orientation by representing the push-history as an orientation histogram. By tracking the history of directions pushed for each object cluster we can build evidence that a cluster cannot be further separated. We present quantitative and qualitative experimental results performed in a real home environment by a mobile manipulator using input from an RGB-D camera mounted on the robot's head. We show that our pushing strategy can more reliably obtain singulation in fewer pushes than an approach, that does not explicitly reason about boundary information.

Original languageEnglish (US)
Title of host publication2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
Number of pages8
StatePublished - 2012
Externally publishedYes
Event25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012 - Vilamoura, Algarve, Portugal
Duration: Oct 7 2012Oct 12 2012

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866


Other25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
CityVilamoura, Algarve

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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