Schulz, RodrigoGuerrero, PabloBustos, BenjaminIoannis Pratikakis and Florent Dupont and Maks Ovsjanikov2017-04-222017-04-222017978-3-03868-030-71997-0471https://doi.org/10.2312/3dor.20171060https://diglib.eg.org:443/handle/10.2312/3dor20171060Three-dimensional descriptors are a common tool nowadays, used in a wide range of tasks. Most of the descriptors that have been proposed in the literature focus on tasks such as object recognition and identification. This paper proposes a novel three-dimensional local descriptor, structured as a set of histograms of the curvature observed on the surface of the object in different directions. This descriptor is designed with a focus on the resolution of the robotic grasping problem, especially on the determination of the orientation required to grasp an object. We validate our proposal following a data-driven approach using grasping information and examples generated using the Gazebo simulator and a simulated PR2 robot. Experimental results show that the proposed descriptor is well suited for the grasping problem, exceeding the performance observed with recent descriptors.I.3.5 [Computer Graphics]Computational Geometry and Object ModelingCurvesurfacesolidand object representationsI.2.9 [Artificial Intelligence]RoboticsManipulatorsI.4.7 [Image Processing and Computer Vision]Feature MeasurementSize and shapes10.2312/3dor.20171060113-120