Name
Abstract | ||
|---|---|---|
In this paper, we present a vision system for robotic object manipulation tasks in natural, domestic environments. Given complex fetch-and-carry robot tasks, the issues related to the whole detect-approach-grasp loop are considered. Our vision system integrates a number of algorithms using monocular and binocular cues to achieve robustness in realistic settings. The cues are considered and used in connection to both foveal and peripheral vision to provide depth information, segmentation of the object(s) of interest, object recognition, tracking and pose estimation. One important property of the system is that the step from object recognition to pose estimation is completely automatic combining both appearance and geometric models. Experimental evaluation is performed in a realistic indoor environment with occlusions, clutter, changing lighting and background conditions. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.robot.2005.03.011 | Robotics and Autonomous Systems |
Keywords | Field | DocType |
Cognitive systems,Object recognition,Service robots,Object manipulation | Computer vision,3D single-object recognition,Machine vision,Computer science,Simulation,3D pose estimation,Pose,Peripheral vision,Artificial intelligence,Articulated body pose estimation,Depth perception,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
52 | 1 | 0921-8890 |
Citations | PageRank | References |
40 | 1.89 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danica Kragic | 1 | 60 | 3.20 |
| Mårten Björkman | 2 | 202 | 13.90 |
| Henrik I. Christensen | 3 | 2848 | 235.82 |
| Jan-Olof Eklundh | 4 | 1125 | 376.36 |