Robotic co-manipulation of deformable linear objects for large deformation tasks - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Article Dans Une Revue Robotics and Autonomous Systems Année : 2024

Robotic co-manipulation of deformable linear objects for large deformation tasks

Résumé

This research addresses the challenge of large/complex deformation in the shape control tasks of Deformable Linear Objects (DLO). We propose a collaborative approach using two manipulators to achieve shape control of a DLO in 2D workspace. The proposed methodology introduces an innovative Intermediary Shapes Generation (ISG) algorithm which outputs a series of intermediary shapes to guide the DLO towards the desired shape. The robot controller is formulated as an optimization problem, where the main objective is to minimize the error between the current shape and the desired shape, while ensuring the diminishing rigidity property of the DLO as a constraint. We conduct extensive simulations and real-life experiments to evaluate the effectiveness of our approach. We consider various scenarios of basic shapes, as well as complex deformations with opposite concavities between initial and final shapes. The outcomes demonstrate the robustness and high accuracy of the proposed system, in achieving complex deformations. This capability represents the primary contribution of our research. The optimization-based control framework, coupled with the ISG algorithm, enables effective shape control without the need for extensive modeling nor training, and offers a promising solution for practical applications requiring precise shape control of DLOs. Moreover, we carry out a thorough review and comparative analysis encompassing the latest literature in DLO shape control, and the techniques for DLO modeling.
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Dates et versions

lirmm-04675678 , version 1 (22-08-2024)

Identifiants

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Karam Almaghout, Andrea Cherubini, Alexandr Klimchik. Robotic co-manipulation of deformable linear objects for large deformation tasks. Robotics and Autonomous Systems, 2024, 175, pp.104652. ⟨10.1016/j.robot.2024.104652⟩. ⟨lirmm-04675678⟩
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