A surface-based Next-Best-View approach for automated 3D model completion of unknown objects

The procedure of manually generating a 3D model of an object is very time consuming for a human operator. Next-best- view (NBV) planning is an important aspect for automation of this procedure in a robotic environment. We propose a surface-based NBV approach, which creates a triangle surface from a real-time data stream and determines viewpoints similar to human intuition. Thereby, the boundaries in the surface are detected and a quadratic patch for each boundary is estimated. Then several viewpoint candidates are calculated, which look perpendicular to the surface and overlap with previous sensor data. A NBV is selected with the goal to fill areas which are occluded. This approach focuses on the completion of a 3D model of an unknown object. Thereby, the search space for the viewpoints is not restricted to a cylinder or sphere. Our NBV determination proves to be very fast, and is evaluated in an experiment on test objects, applying an industrial robot and a laser range scanner.

[1]  Kenji KANEKO,et al.  Humanoid robot HRP-3 , 2004, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Richard Pito,et al.  A Solution to the Next Best View Problem for Automated Surface Acquisition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Ruzena Bajcsy,et al.  Occlusions as a Guide for Planning the Next View , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Benjamin Loriot,et al.  Non-Model Based Method for an Automation of 3D Acquisition and Post-Processing , 2009 .

[5]  Andrew J. Davison,et al.  Live dense reconstruction with a single moving camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Sören Larsson,et al.  Path planning for laser scanning with an industrial robot , 2008, Robotics Auton. Syst..

[7]  Christophe Dumont,et al.  A next-best-view system for autonomous 3-D object reconstruction , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[8]  Florian Schmidt,et al.  Rollin' Justin - Mobile platform with variable base , 2009, 2009 IEEE International Conference on Robotics and Automation.

[9]  G. Roth,et al.  View planning for automated three-dimensional object reconstruction and inspection , 2003, CSUR.

[10]  Shengyong Chen,et al.  Active Sensor Planning for Multiview Vision Tasks , 2008 .

[11]  Michael Suppa.  Autonomous robot work cell exploration using multisensory eye-in-hand systems , 2008 .

[12]  Gerd Hirzinger,et al.  Tackling multi-sensory 3D data acquisition and fusion , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Frank P. Ferrie,et al.  Autonomous exploration: driven by uncertainty , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  François Blais.  Review of 20 years of range sensor development , 2004, J. Electronic Imaging.

[15]  Tim Bodenmüller,et al.  Streaming surface reconstruction from real time 3D-measurements , 2009 .

[16]  Paolo Cignoni,et al.  RoboScan: an automatic system for accurate and unattended 3D scanning , 2004, Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004..

[17]  Gerd Hirzinger,et al.  The 3D-Modeller: A Multi-Purpose Vision Platform , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[18]  Tim Weyrich,et al.  Post-processing of Scanned 3D Surface Data , 2004, PBG.

[19]  Youfu Li,et al.  A Novel View Planning Method for Automatic Reconstruction of Unknown 3-D Objects Based on the Limit Visual Surface , 2009, 2009 Fifth International Conference on Image and Graphics.

[20]  Olivier Stasse,et al.  A two-steps next-best-view algorithm for autonomous 3D object modeling by a humanoid robot , 2009, 2009 IEEE International Conference on Robotics and Automation.