We describe Roboscan, a Robot cell that combines-2D and 3D vision in a simple device, to aid a Robot manipulator in pick-and-place operations in a fast and accurate way. The optical head of Roboscan combines the two vision systems: the camera is used “stand-alone” in the 2D system, and combined to a laser slit projector in the 3D system, which operates in the triangulation mode. The 2D system, using suitable libraries, provides the preliminary 2D information to the 3D system to perform in a very fast, flexible and robust way the point cloud segmentation and fitting. Roboscan is mounted onto an anthropomorphic, 6-DOF Robot manipulator. The most innovative part of the system is represented by the use of robust 2D geometric template matching as a mean to classify 3D objects. In this way we avoid time-consuming 3D point cloud segmentation and 3D object classification, using 3D data only for estimating pose and orientation of the robot gripper. In addition, a novel approach to the template definition in the 2D geometric template matching is proposed, where the influence of surface reflectance and colour of the objects over the definition of the template geometry is minimized. We describe the procedures for 2D and 3D vision of Roboscan, together with the calibration procedures that have been implemented. We also present a set of tests that show the performance of the system and its effectiveness in a number of pick-and-place operations.
Roboscan: a combined 2D and 3D vision system for improved speed and flexibility in pick-and-place operation
DOCCHIO, Franco;SANSONI, Giovanna
2013-01-01
Abstract
We describe Roboscan, a Robot cell that combines-2D and 3D vision in a simple device, to aid a Robot manipulator in pick-and-place operations in a fast and accurate way. The optical head of Roboscan combines the two vision systems: the camera is used “stand-alone” in the 2D system, and combined to a laser slit projector in the 3D system, which operates in the triangulation mode. The 2D system, using suitable libraries, provides the preliminary 2D information to the 3D system to perform in a very fast, flexible and robust way the point cloud segmentation and fitting. Roboscan is mounted onto an anthropomorphic, 6-DOF Robot manipulator. The most innovative part of the system is represented by the use of robust 2D geometric template matching as a mean to classify 3D objects. In this way we avoid time-consuming 3D point cloud segmentation and 3D object classification, using 3D data only for estimating pose and orientation of the robot gripper. In addition, a novel approach to the template definition in the 2D geometric template matching is proposed, where the influence of surface reflectance and colour of the objects over the definition of the template geometry is minimized. We describe the procedures for 2D and 3D vision of Roboscan, together with the calibration procedures that have been implemented. We also present a set of tests that show the performance of the system and its effectiveness in a number of pick-and-place operations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
