Modeling of Inverse Kinematic of 3-DoF Robot, Using Unit Quaternions and Artificial Neural Network

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dc.contributor.authorEusebio Jiménez López
dc.contributor.authorDaniel Servín de la Mora-Pulido
dc.contributor.authorLuis Alfonso Reyes-Ávila
dc.contributor.authorRaúl Servín de la Mora-Pulido
dc.contributor.authorJavier Melendez-Campos
dc.contributor.authorAldo López-Martínez
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:15:12Z
dc.date.available2026-03-22T14:15:12Z
dc.date.issued2021
dc.descriptionCitaciones: 23
dc.description.abstractSUMMARY This paper presents a novel method for modeling a 3-degree of freedom open kinematic chain using quaternions algebra and neural network to solve the inverse kinematic problem. The structure of the network was composed of 3 hidden layers with 25 neurons per layer and 1 output layer. The network was trained using the Bayesian regularization backpropagation. The inverse kinematic problem was modeled as a system of six nonlinear equations and six unknowns. Finally, both models were tested using a straight path to compare the results between the Newton–Raphson method and the network training.
dc.identifier.doi10.1017/s0263574720001071
dc.identifier.urihttps://doi.org/10.1017/s0263574720001071
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/45430
dc.language.isoen
dc.publisherCambridge University Press
dc.relation.ispartofRobotica
dc.sourceUniversidad Tecnológica del Sur de Sonora
dc.subjectKinematics
dc.subjectInverse kinematics
dc.subjectArtificial neural network
dc.subjectBackpropagation
dc.subjectQuaternion
dc.subjectNonlinear system
dc.subjectRegularization (linguistics)
dc.subjectComputer science
dc.subjectInverse
dc.subjectKinematics equations
dc.titleModeling of Inverse Kinematic of 3-DoF Robot, Using Unit Quaternions and Artificial Neural Network
dc.typearticle

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