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

Torea Foissotte (1, 2) , Olivier Stasse (2) , Adrien Escande (2) , Pierre-Brice Wieber (2, 3) , Abderrahmane Kheddar (2, 1)

1 IDH - Interactive Digital Humans
2 CNRS-AIST JRL - Joint Robotics Laboratory
3 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems

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.

Domaines: Robotique [cs.RO]

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⟩