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Conference Papers Year : 2009

A Two-Steps Next-Best-View Algorithm for Autonomous 3D Object Modeling by a Humanoid Robot

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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.
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Dates and versions

inria-00390587 , version 1 (02-06-2009)

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Torea Foissotte, Olivier Stasse, Adrien Escande, Pierre-Brice Wieber, Abderrahmane Kheddar. A Two-Steps Next-Best-View Algorithm for Autonomous 3D Object Modeling by a Humanoid Robot. ICRA'2009: International Conference on Robotics and Automation, May 2009, Kobe, Japan. pp.1159-1164, ⟨10.1109/ROBOT.2009.5152350⟩. ⟨inria-00390587⟩
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