We propose a complete system for 3D object reconstruction and grasping based on an articulated robotic manipulator. We deploy an RGB-D sensor as an end effector placed directly on the robotic arm, and process the acquired data to perform multi-view 3D reconstruction and object grasping. We leverage the high repeatability of the robotic arm to estimate 3D camera poses with millimeter accuracy and control each of the six sensor’s DOF in a dexterous workspace. Thereby, we can estimate camera poses directly by robot kinematics and deploy a Truncated Signed Distance Function (TSDF) to accurately fuse multiple views into a unified 3D reconstruction of the scene. Then, we propose an efficient approach to segment the sought objects out of a planar workbench as well as a novel algorithm to automatically estimate grasping points.

RobotFusion: Grasping with a robotic manipulator via multi-view reconstruction / de Gregorio, Daniele; Tombari, Federico; Di Stefano, Luigi. - ELETTRONICO. - 9915:(2016), pp. 634-647. (Intervento presentato al convegno 14th European Conference on Computer Vision, ECCV 2016 tenutosi a nld nel 2016) [10.1007/978-3-319-49409-8_54].

RobotFusion: Grasping with a robotic manipulator via multi-view reconstruction

DE GREGORIO, DANIELE;TOMBARI, FEDERICO;DI STEFANO, LUIGI
2016

Abstract

We propose a complete system for 3D object reconstruction and grasping based on an articulated robotic manipulator. We deploy an RGB-D sensor as an end effector placed directly on the robotic arm, and process the acquired data to perform multi-view 3D reconstruction and object grasping. We leverage the high repeatability of the robotic arm to estimate 3D camera poses with millimeter accuracy and control each of the six sensor’s DOF in a dexterous workspace. Thereby, we can estimate camera poses directly by robot kinematics and deploy a Truncated Signed Distance Function (TSDF) to accurately fuse multiple views into a unified 3D reconstruction of the scene. Then, we propose an efficient approach to segment the sought objects out of a planar workbench as well as a novel algorithm to automatically estimate grasping points.
2016
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
634
647
RobotFusion: Grasping with a robotic manipulator via multi-view reconstruction / de Gregorio, Daniele; Tombari, Federico; Di Stefano, Luigi. - ELETTRONICO. - 9915:(2016), pp. 634-647. (Intervento presentato al convegno 14th European Conference on Computer Vision, ECCV 2016 tenutosi a nld nel 2016) [10.1007/978-3-319-49409-8_54].
de Gregorio, Daniele; Tombari, Federico; Di Stefano, Luigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/589906
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