{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:23:25Z","timestamp":1754155405170,"version":"3.41.2"},"reference-count":36,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2014,10,20]],"date-time":"2014-10-20T00:00:00Z","timestamp":1413763200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,10,20]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 The aim of this paper is to present a novel methodology which incorporates Camshift, Kalman filter (KFs) and adaptive multi-space transformation (AMT) for a human-robot interface, which perfects human intelligence and teleoperation. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 In the proposed method, an inertial measurement unit is used to measure the orientation of the human hand, and a Camshift algorithm is used to track the human hand using a three-dimensional camera. Although the location and the orientation of the human can be obtained from the two sensors, the measurement error increases over time due to the noise of the devices and the tracking errors. KFs are used to estimate the location and the orientation of the human hand. Moreover, to be subject to the perceptive limitations and the motor limitations, human operator is hard to carry out the high precision operation. An AMT method is proposed to assist the operator to improve accuracy and reliability in determining the pose of the robot. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 The experimental results show that this method would not hinder most natural human-limb motion and allows the operator to concentrate on his\/her own task. Compared with the non-contacting marker-less method (Kofman <jats:italic>et al.<\/jats:italic>, 2007), this method proves more accurate and stable. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 The human-robot interface system was experimentally verified in a laboratory environment, and the results indicate that such a system can complete high-precision manipulation efficiently.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/ir-05-2014-0336","type":"journal-article","created":{"date-parts":[[2014,10,31]],"date-time":"2014-10-31T09:14:11Z","timestamp":1414746851000},"page":"585-595","source":"Crossref","is-referenced-by-count":3,"title":["A novel human-robot interface using hybrid sensors with Kalman filters"],"prefix":"10.1108","volume":"41","author":[{"given":"Ping","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Guanglong","family":"Du","sequence":"additional","affiliation":[]},{"given":"Di","family":"Li","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020122802363059400_b1","doi-asserted-by":"crossref","unstructured":"Ando, T.\n               , \n                  Tsukahara, R.\n                and \n                  Seki, M.\n                (2012), \u201cA hapic interface \u201cforce blinker 2\u201d for navigation of the visually impaired\u201d, \n                  IEEE Transactions on Industrial Electronics\n               , Vol. 59 No. 11, pp. 4112-4119.","DOI":"10.1109\/TIE.2011.2173894"},{"key":"key2020122802363059400_b3","doi-asserted-by":"crossref","unstructured":"Borghese, N.A.\n                and \n                  Rigiroli, P.\n                (2002), \u201cTracking densely moving markers\u201d, \n                 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