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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Foissotte, T. Stasse, O. Escande, A. Wieber, P.-B. Kheddar, A. |
| Copyright Year | 2009 |
| Description | Author affiliation: CNRS-AIST JRL, UMI3218/CRT, Tsukuba, Japan (Stasse, O.; Escande, A.) || INRIA Rhône-Alpes, France (Wieber, P.-B.) || CNRS-UM2 LIRMM, Montpellier, France (Foissotte, T.; Kheddar, A.) |
| Abstract | A novel approach is presented which aims at building autonomously visual models of unknown objects, using a humanoid robot. Previous methods have been proposed for the specific problem of the next-best-view during the modeling and the recognition process. However our approach differs as it takes advantage of humanoid specificities in terms of embedded vision sensor and redundant motion capabilities. In a previous work, another approach to this specific problem was presented which relies on a derivable formulation of the visual evaluation in order to integrate it with our posture generation method. However to get rid of some limitations we propose a new method, formulated using two steps: (i) an optimization algorithm without derivatives is used to find a camera pose which maximizes the amount of unknown data visible, and (ii) a whole robot posture is generated by using a different optimization method where the computed camera pose is set as a constraint on the robot head. |
| Starting Page | 1159 |
| Ending Page | 1164 |
| File Size | 3579796 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424427888 |
| ISSN | 10504729 |
| DOI | 10.1109/ROBOT.2009.5152350 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-12 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Humanoid robots Cameras Robot sensing systems Robot vision systems Orbital robotics Stereo vision Object detection Context modeling Robotics and automation Cathode ray tubes |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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