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Communication Dans Un Congrès Année : 2022

3D visual-based tension control in strip-like deformable objects using a catenary model

Résumé

In recent years, there has been a growing interest in robotic manipulation of deformable objects. In order to perform certain tasks, the robot must control the shape of the object while taking care not to apply excessive stresses so as not to deform it irreversibly. This is the case when extracting elasto-plastic objects in strips from an industrial reel. In order to control the mechanical stresses within the object, we propose a vision-based control scheme to minimize tension by regulating the angular velocity of a motorized reel on which they are wound. In this paper, we propose a method, based on a catenary model and visual feedback from a low-cost RGB-D camera, to estimate the tension distribution along a rubber strip. Thus, the control strategy aims to achieve a desired tension value by varying the length of the suspended portion of the manipulated strip. Simulation and experimental results validate the proposed approach for strip-like objects of various dimensions.
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Dates et versions

hal-03890015 , version 1 (08-12-2022)

Identifiants

Citer

N. Roca Filella, Adrien Koessler, B.C. Bouzgarrou, Juan Antonio Corrales Ramon. 3D visual-based tension control in strip-like deformable objects using a catenary model. 35th IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2022, Kyoto, Japan. pp.3210-3217, ⟨10.1109/IROS47612.2022.9982197⟩. ⟨hal-03890015⟩
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