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Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot de...

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Autores principales: Rodriguez-Donate, Carlos, Osornio-Rios, Roque Alfredo, Rivera-Guillen, Jesus Rooney, de Jesus Romero-Troncoso, Rene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231324/
https://www.ncbi.nlm.nih.gov/pubmed/22163850
http://dx.doi.org/10.3390/s110404335
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author Rodriguez-Donate, Carlos
Osornio-Rios, Roque Alfredo
Rivera-Guillen, Jesus Rooney
de Jesus Romero-Troncoso, Rene
author_facet Rodriguez-Donate, Carlos
Osornio-Rios, Roque Alfredo
Rivera-Guillen, Jesus Rooney
de Jesus Romero-Troncoso, Rene
author_sort Rodriguez-Donate, Carlos
collection PubMed
description Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot.
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spelling pubmed-32313242011-12-07 Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots Rodriguez-Donate, Carlos Osornio-Rios, Roque Alfredo Rivera-Guillen, Jesus Rooney de Jesus Romero-Troncoso, Rene Sensors (Basel) Article Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot. Molecular Diversity Preservation International (MDPI) 2011-04-13 /pmc/articles/PMC3231324/ /pubmed/22163850 http://dx.doi.org/10.3390/s110404335 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Rodriguez-Donate, Carlos
Osornio-Rios, Roque Alfredo
Rivera-Guillen, Jesus Rooney
de Jesus Romero-Troncoso, Rene
Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title_full Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title_fullStr Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title_full_unstemmed Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title_short Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
title_sort fused smart sensor network for multi-axis forward kinematics estimation in industrial robots
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231324/
https://www.ncbi.nlm.nih.gov/pubmed/22163850
http://dx.doi.org/10.3390/s110404335
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