Details

Autor(en) / Beteiligte

• Delmerico, Jeffrey
• Isler, Stefan
• Sabzevari, Reza
• Scaramuzza, Davide

Titel

A comparison of volumetric information gain metrics for active 3D object reconstruction

Ist Teil von

• Autonomous robots, 2018-02, Vol.42 (2), p.197-208

Ort / Verlag

New York: Springer US

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In this paper, we investigate the following question: when performing next best view selection for volumetric 3D reconstruction of an object by a mobile robot equipped with a dense (camera-based) depth sensor, what formulation of information gain is best? To address this question, we propose several new ways to quantify the volumetric information  (VI) contained in the voxels of a probabilistic volumetric map, and compare them to the state of the art with extensive simulated experiments. Our proposed formulations incorporate factors such as visibility likelihood and the likelihood of seeing new parts of the object. The results of our experiments allow us to draw some clear conclusions about the VI formulations that are most effective in different mobile-robot reconstruction scenarios. To the best of our knowledge, this is the first comparative survey of VI formulation performance for active 3D object reconstruction. Additionally, our modular software framework is adaptable to other robotic platforms and general reconstruction problems, and we release it open source for autonomous reconstruction tasks.