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Forward Kinematics for Suspended Under-Actuated Cable-Driven Parallel Robots: A Neural Network Approach

Abstract : Kinematic analysis of under-constrained Cable-Driven Parallel Robots has been a topic of interest because of the inherent coupling between the loop-closure and static equilibrium equations. The paper proposes an unsupervised neural network algorithm to perform real-time forward geometrico-static analysis of such robots in a suspended configuration under the action of gravity. The formulation determines a non-linear function approximation to model the problem and proves to be efficient in solving for consecutive and close waypoints in a path. The methodology is applied on a six-degree-of-freedom (6-DOF) spatial under-constrained suspended cable-driven parallel robot. Specific comparison results to show the effectiveness of the proposed method in tracking a given path and degree of constraint satisfaction are presented against the results obtained from nonlinear least-square optimization.
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Contributor : Stéphane Caro Connect in order to contact the contributor
Submitted on : Friday, September 17, 2021 - 6:30:54 PM
Last modification on : Wednesday, October 13, 2021 - 3:52:07 PM

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  • HAL Id : hal-03348135, version 1

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Utkarsh Mishra, Stéphane Caro. Forward Kinematics for Suspended Under-Actuated Cable-Driven Parallel Robots: A Neural Network Approach. The ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2021, 45th Mechanisms and Robotics Conference (MR), Aug 2021, Online, United States. ⟨hal-03348135⟩

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