Markerless Augmented Reality for Robotic Helicoptor Applications
Identifieur interne : 000984 ( Main/Merge ); précédent : 000983; suivant : 000985Markerless Augmented Reality for Robotic Helicoptor Applications
Auteurs : Ian Yen-Hung Chen [Nouvelle-Zélande] ; Bruce Macdonald [Nouvelle-Zélande] ; Burkhard Wünsche [Nouvelle-Zélande]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: The objective of this research is to apply markerless Augmented Reality (AR) techniques to aid in the visualisation of robotic helicopter related tasks. Conventional robotic AR applications work well with markers in prepared environments but are infeasible in outdoor settings. In this paper, we present preliminary results from a real time markerless AR system for tracking natural features in an agricultural scene. By constructing a virtual marker under a known initial configuration of the robotic helicopter, camera and the ground plane, the camera pose can be continuously tracked using the natural features from the image sequence to perform augmentation of virtual objects. The experiments are simulated on a mock-up model of an agricultural farm and the results show that the current AR system is capable of tracking the camera pose accurately for translational motions and roll rotations. Future work includes reducing jitter in the virtual marker vertices to improve camera pose estimation accuracy for pitch and yaw rotations, and implementing feature recovery algorithms.
Url:
DOI: 10.1007/978-3-540-78157-8_10
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<front><div type="abstract" xml:lang="en">Abstract: The objective of this research is to apply markerless Augmented Reality (AR) techniques to aid in the visualisation of robotic helicopter related tasks. Conventional robotic AR applications work well with markers in prepared environments but are infeasible in outdoor settings. In this paper, we present preliminary results from a real time markerless AR system for tracking natural features in an agricultural scene. By constructing a virtual marker under a known initial configuration of the robotic helicopter, camera and the ground plane, the camera pose can be continuously tracked using the natural features from the image sequence to perform augmentation of virtual objects. The experiments are simulated on a mock-up model of an agricultural farm and the results show that the current AR system is capable of tracking the camera pose accurately for translational motions and roll rotations. Future work includes reducing jitter in the virtual marker vertices to improve camera pose estimation accuracy for pitch and yaw rotations, and implementing feature recovery algorithms.</div>
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