Paper Info
Title
A two-steps next-best-view algorithm for autonomous 3D object modeling by a humanoid robot
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.
Year
DOI
Venue
2009
10.1109/ROBOT.2009.5152350
ICRA
Keywords
Field
DocType
different optimization method,novel approach,posture generation method,object modeling,two-steps next-best-view algorithm,previous method,autonomously visual model,new method,robot head,humanoid robot,whole robot posture,specific problem,pose estimation,data mining,object recognition,stereo vision,humanoid robots,context modeling,object model,cathode ray tubes,pixel
Object detection,Computer vision,Computer science,Object model,Pose,Pixel,Optimization algorithm,Artificial intelligence,Robot,Humanoid robot,Cognitive neuroscience of visual object recognition
Conference
ISSN
Citations 
PageRank 
1050-4729
9
0.67
References 
Authors
9
5
Name
Order
Citations
PageRank
Torea Foissotte1241.73
Olivier Stasse2143885.86
Adrien Escande327322.91
Pierre-Brice Wieber430222.93
Abderrahmane Kheddar51191101.66