Model Based Tracking and Pose Estimation

 

A robotic manipulation of objects typically involves object detection/recognition, servoing to the object, alignment and grasping. To perform fine alignment and finally grasping, it is usually necessary to estimate position and orientation (pose) of the object. We have developed a model based tracking system that estimates and continuously update the pose of the object to be manipulated. Here, a wire-frame model is used to find and track features in the consequent images. One of the important parts of the system is the ability to automatically initiate the tracking process. The strength of the system is the ability to operate in a realisticm indoor environment with changing lighting and background conditions.

 

 

Related Publications

Object Recognition and Pose Estimation using Color Cooccurrence Histograms and Geometric Modeling
(S. Ekvall, D. Kragic and F. Hoffmann)
Image and Vision Computing, Volume 23, Issue 11, pp 943-955, October 2005

Initialization and System Modeling in 3-D Pose Tracking
(D. Kragic and V. Kyrki)
In IEEE International Conference on Pattern Recognition 2006. ICPR'06, Hong Kong, China

Tracking Unobservable Rotations by Cue Integration
(V. Kyrki and D. Kragic)
In IEEE International Conference on Robotics and Automation 2006. ICRA'06, Orlando, USA

Robust Statistics for 3D Object Tracking
(P. Preisig and D. Kragic)
In IEEE International Conference on Robotics and Automation 2006. ICRA'06, Orlando, USA

Robust Real-Time Visual Tracking: Comparison, Unification and Performance Evaluation
(A. Comport, D. Kragic, E. Marchand and F. Chaumette)
In IEEE International Conference on Robotics and Automation, 2005. ICRA'05, Barcelona, Spain

Integration of Model-based and Model-free Cues for Visual Object Tracking in 3D
(V. Kyrki and D. Kragic)
In IEEE International Conference on Robotics and Automation, 2005. ICRA'05, Barcelona, Spain

Confluence of Parameters in Model-Based Tracking
(Danica Kragic and Henrik I. Christensen)
In IEEE International Conference on Robotics and Automation , ICRA 2003, Taipei, Taiwan

Model Based Techniques for Robotic Servoing and Grasping
(Danica Kragic and Henrik I. Christensen )
In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002. IROS'02,
Lausanne, Switzerland

Details

Weak Models and Cue-Integration for Real-Time Tracking
(Danica Kragic and Henrik I Christensen)
In IEEE International Conference on Robotics and Automation , ICRA 2002, Washington, USA

RealTime Tracking Meets Online Grasp Planning
(Danica Kragic, Andrew Miller and Peter Allen)
In IEEE International Conference on Robotics and Automation , ICRA 2001, Seoul, Korea


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