The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Robust perception is a vital capability for robotic manipulation in unstructured scenes. In this context, full pose estimation of relevant objects in a scene is a critical step towards the introduction of robots into household environments. In this paper, we present an approach for building metric 3D models of objects using local descriptors from several images. Each model is optimized to fit a set of calibrated training images, thus obtaining the best possible alignment between the 3D model and the real object. Given a new test image, we match the local descriptors to our stored models online, using a novel combination of the RANSAC and Mean Shift algorithms to register multiple instances of each object. A robust initialization step allows for arbitrary rotation, translation and scaling of objects in the test images. The resulting system provides markerless 6-DOF pose estimation for complex objects in cluttered scenes. We provide experimental results demonstrating orientation and translation accuracy, as well a physical implementation of the pose output being used by an autonomous robot to perform grasping in highly cluttered scenes.

Notes

Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics

Associated Lab(s) / Group(s): Personal Robotics

Number of pages: 8

Text Reference

Alvaro Collet Romea, Dmitry Berenson, Siddhartha Srinivasa, and David Ferguson, "Object Recognition and Full Pose Registration from a Single Image for Robotic Manipulation," IEEE International Conference on Robotics and Automation (ICRA '09), May, 2009.

BibTeX Reference

@inproceedings{Collet_Romea_2009_6301,
   author = "Alvaro {Collet Romea} and Dmitry Berenson and Siddhartha Srinivasa and David Ferguson",
   title = "Object Recognition and Full Pose Registration from a Single Image for Robotic Manipulation",
   booktitle = "IEEE International Conference on Robotics and Automation (ICRA '09)",
   month = "May",
   year = "2009",
}

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