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Noise characterization of depth sensors for surface inspections

Abstract : In the context of environment reconstruction for inspection, it is important to handle sensor noise properly to avoid distorted representations. A short survey of available sensors is realize to help their selection based on the payload capability of a robot. We then propose uncertainty models based on empirical results for three models of laser rangefinders: Hokuyo URG-04LX, UTM-30LX and the Sick LMS-151. The methodology, used to characterize those sensors, targets more specifically different metallic materials which often give distorted images due to reflexion. We also evaluate the impact of sensor noise on surface normal vector reconstruction and conclude with observations about the impact of sunlight and reflexions.
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François Pomerleau, Andreas Breitenmoser, Ming Liu, Francis Colas, Roland Siegwart. Noise characterization of depth sensors for surface inspections. 2nd International Conference on Applied Robotics for the Power Industry (CARPI), 2012, Zurich, Switzerland. ⟨10.1109/CARPI.2012.6473358⟩. ⟨hal-01142707⟩



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