Title :
Combined shape, appearance and silhouette for simultaneous manipulator and object tracking
Author :
Hebert, Paul ; Hudson, Nicolas ; Ma, Jeremy ; Howard, Thomas ; Fuchs, Thomas ; Bajracharya, Max ; Burdick, Joel
Author_Institution :
California Inst. of Technol., Pasadena, CA, USA
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™WAM manipulator.
Keywords :
Kalman filters; drilling; image sensors; industrial manipulators; nonlinear filters; object tracking; robot vision; stereo image processing; 3D ranging sensors; Barret WAM manipulator; DARPA ARM-S drilling test; DARPA ARM-S system; appearance feature; autonomous robots; estimation framework; imaging sensors; object tracking; object-fixed frame location; palm frame location; reference frame tracking; robot arm; shape feature; silhouette feature; simultaneous manipulator; stereo cameras; unscented Kalman Filter; Cameras; Joints; Manipulators; Mathematical model; Robot sensing systems; Visualization;
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
DOI :
10.1109/ICRA.2012.6225084