{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T06:56:23Z","timestamp":1768719383750,"version":"3.49.0"},"reference-count":28,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2019,8,21]],"date-time":"2019-08-21T00:00:00Z","timestamp":1566345600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IR"],"published-print":{"date-parts":[[2019,8,21]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>This paper aims to provide a simple and flexible calibration method of parallel manipulators for improving the position accuracy only using partial pose information.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The overall idea of this method is to use BP neural network to fit the relationship between calibration parameters and measurement parameters and then adjust calibration parameters according to measurements.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The calibration method significantly improves the position accuracy of the six-axis parallel manipulator. Simulation shows that the accuracy can be improved by increasing the number of positions consisted of samples to train BP neural network, and when the position number is increased, the descent velocity of fitting error is decreased.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The method is general for various parallel mechanisms and simple for measurement process. It can be applied to the calibration of various mechanisms without analyzing the mathematical relationship between measurements and calibration parameters. The measurement parameters can be flexibly selected to simplify measurement process, which saves calibration cost and time.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ir-12-2018-0248","type":"journal-article","created":{"date-parts":[[2019,8,21]],"date-time":"2019-08-21T08:09:10Z","timestamp":1566374950000},"page":"692-698","source":"Crossref","is-referenced-by-count":27,"title":["Calibration of a six-axis parallel manipulator based on BP neural network"],"prefix":"10.1108","volume":"46","author":[{"given":"Dianjin","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Guangyu","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Longqiu","family":"Li","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2019,8,21]]},"reference":[{"issue":"6","key":"key2022103114490157000_ref001","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1016\/j.rcim.2010.05.007","article-title":"Experimental kinematic calibration of parallel manipulators using a relative position error measurement system","volume":"26","year":"2010","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"issue":"8","key":"key2022103114490157000_ref002","first-page":"148","article-title":"Neural network solutions for forward kinematics problem of hybrid serial\u2013parallel manipulator","volume":"1","year":"2013","journal-title":"The Scientific World Journal"},{"issue":"1","key":"key2022103114490157000_ref003","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s12532-016-0109-7","article-title":"On efficiently combining limited-memory and trust-region techniques","volume":"9","year":"2017","journal-title":"Mathematical Programming Computation"},{"key":"key2022103114490157000_ref004","first-page":"4666","article-title":"Kinematic calibration of a Gough-Stewart platform using an omnidirectional camera","volume-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems","year":"2006"},{"key":"key2022103114490157000_ref005","first-page":"147","article-title":"Optimal measurement configurations for Gough platform calibration","year":"2002"},{"key":"key2022103114490157000_ref006","first-page":"4214","article-title":"Neural network solution for forward kinematics problem of HEXA parallel robot","volume-title":"American Control Conference","year":"2008"},{"issue":"3","key":"key2022103114490157000_ref007","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1108\/IR-07-2013-376","article-title":"Vision-based calibration of a hexa parallel robot","volume":"41","year":"2014","journal-title":"Industrial Robot: An International Journal"},{"key":"key2022103114490157000_ref008","first-page":"2797","article-title":"Calibration method and experiment of Stewart platform using a laser tracker","year":"2003"},{"key":"key2022103114490157000_ref009","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/978-3-319-61431-1_15","article-title":"Improving the forward kinematics of cable-driven parallel robots through cable angle sensors","volume":"53","year":"2018","journal-title":"Cable-Driven Parallel Robots"},{"key":"key2022103114490157000_ref010","volume-title":"Neural Network Design","year":"1996"},{"key":"key2022103114490157000_ref011","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.mechmachtheory.2018.03.019","article-title":"Kinematic calibration of a 6-DOF parallel manipulator based on identifiable parameters separation (IPS)","volume":"126","year":"2018","journal-title":"Mechanism and Machine Theory"},{"issue":"4","key":"key2022103114490157000_ref012a","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1108\/01439911211227971","article-title":"Kinematic calibration of a 3-DOF planar parallel robot","volume":"39","year":"2012","journal-title":"Industrial Robot: An International Journal"},{"key":"key2022103114490157000_ref012","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/978-981-10-8597-0_14","article-title":"Forward kinematics of the 3-RPRS parallel manipulator using a geometric approach","volume-title":"Machines, Mechanism and Robotics","year":"2019"},{"key":"key2022103114490157000_ref013","unstructured":"Li, Y., Xie, X., Shan, L., Ma, D. and Zhang, D. 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