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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title An Information Gain Formulation for Active Volumetric 3D Reconstruction
Organization Unit
Authors
  • Stefan Isler
  • Reza Sabzevari
  • Jeffrey Delmerico
  • Davide Scaramuzza
Presentation Type paper
Item Subtype Original Work
Refereed No
Status Published in final form
Language
  • English
Page Range 3477 - 3484
Event Title IEEE International Conference on Robotics and Automation (ICRA)
Event Type conference
Event Location Stockholm, Sweden
Event Start Date May 16 - 2016
Event End Date May 21 - 2016
Place of Publication Stockholm, Sweden
Publisher Institute of Electrical and Electronics Engineers
Abstract Text We consider the problem of next-best view selection for volumetric reconstruction of an object by a mobile robot equipped with a camera. Based on a probabilistic volumetric map that is built in real time, the robot can quantify the expected information gain from a set of discrete candidate views. We propose and evaluate several formulations to quantify this information gain for the volumetric reconstruction task, including visibility likelihood and the likelihood of seeing new parts of the object. These metrics are combined with the cost of robot movement in utility functions. The next best view is selected by optimizing these functions, aiming to maximize the likelihood of discovering new parts of the object. We evaluate the functions with simulated and real world experiments within a modular software system that is adaptable to other robotic platforms and reconstruction problems. We release our implementation open source.
Digital Object Identifier 10.1109/ICRA.2016.7487527
Other Identification Number merlin-id:13325
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