@inproceedings{16d4111c8550405ab4a005ce0304c72b,
title = "Combined shape, appearance and silhouette for simultaneous manipulator and object tracking",
abstract = "This paper develops an estimation framework for sensor-guided manipulation of a rigid object via a robot arm. Using an unscented Kalman Filter (UKF), the method combines dense range information (from stereo cameras and 3D ranging sensors) as well as visual appearance features and silhouettes of the object and manipulator to track both an object-fixed frame location as well as a manipulator tool or palm frame location. If available, tactile data is also incorporated. By using these different imaging sensors and different imaging properties, we can leverage the advantages of each sensor and each feature type to realize more accurate and robust object and reference frame tracking. The method is demonstrated using the DARPA ARM-S system, consisting of a Barrett{\texttrademark}WAM manipulator.",
author = "Paul Hebert and Nicolas Hudson and Jeremy Ma and Thomas Howard and Thomas Fuchs and Max Bajracharya and Joel Burdick",
year = "2012",
month = may,
day = "1",
doi = "10.1109/ICRA.2012.6225084",
language = "English",
isbn = "9781467314039",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2405--2412",
booktitle = "2012 IEEE International Conference on Robotics and Automation, ICRA 2012",
address = "United States",
note = " 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 ; Conference date: 14-05-2012 Through 18-05-2012",
}