In this paper, the estimation of the 3D shape of a deformable linear object such as an electric cable for the purpose of planning suitable grasping poses is proposed. These poses can be then exploited by a robot manipulator to grasp and manipulate the cable for assembling and manufacturing purposes. The proposed method is based on a previously developed algorithm called ARIADNE providing the segmentation and spline modelling on a single image of electric cables even in cluttered scenarios. By exploiting this result and by collecting measurements from different points of view by means of a 2D camera mounted on the robot end effector, a method to estimate the 3D shape of the cable is here presented. This method is experimentally evaluated in different scenarios showing the capability of providing reliable estimation of the cable shape. The result is then used to drive to robot to grasp the cable in controlled positions.

3D DLO Shape Detection and Grasp Planning from Multiple 2D Views / Galassi, Kevin; Palli, Gianluca; Caporali, Alessio. - (2021), pp. 424-429. (Intervento presentato al convegno 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) nel 12-16 July 2021) [10.1109/AIM46487.2021.9517655].

3D DLO Shape Detection and Grasp Planning from Multiple 2D Views

Kevin, Galassi;
2021

Abstract

In this paper, the estimation of the 3D shape of a deformable linear object such as an electric cable for the purpose of planning suitable grasping poses is proposed. These poses can be then exploited by a robot manipulator to grasp and manipulate the cable for assembling and manufacturing purposes. The proposed method is based on a previously developed algorithm called ARIADNE providing the segmentation and spline modelling on a single image of electric cables even in cluttered scenarios. By exploiting this result and by collecting measurements from different points of view by means of a 2D camera mounted on the robot end effector, a method to estimate the 3D shape of the cable is here presented. This method is experimentally evaluated in different scenarios showing the capability of providing reliable estimation of the cable shape. The result is then used to drive to robot to grasp the cable in controlled positions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2972196