{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:24:37Z","timestamp":1760243077215,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2015,6,11]],"date-time":"2015-06-11T00:00:00Z","timestamp":1433980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Virtual simulation technology has been considered as a highly efficient and  cost-effective solution for a soldier training system, and evolved into diverse combinations of hardware and software. To maximize the virtual reality effect within a restricted space, a locomotion interface such as an omni-directional treadmill is introduced as a major component of a virtual simulator, therefore real time interaction between human and the virtual simulator becomes very important. Displacement and heading changes of the trainee are crucial information to control the virtual simulator when we implement highly reactive motion control for the omni-directional treadmill and interaction control of the virtual contents. This paper proposes a control parameter estimation algorithm for the virtual training simulator by using two types of motion capture sensors and presents the experimental results. Kinematic joint positions are analyzed to estimate the trainee\u2019s location and velocity for feedback and feedforward control of the omni-directional treadmill. The accuracy of two approaches is evaluated by comparing with the reference system, which gives a ground truth value.<\/jats:p>","DOI":"10.3390\/sym7021043","type":"journal-article","created":{"date-parts":[[2015,6,11]],"date-time":"2015-06-11T10:44:59Z","timestamp":1434019499000},"page":"1043-1060","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Kinematic Skeleton Based Control of a Virtual Simulator for Military Training"],"prefix":"10.3390","volume":"7","author":[{"given":"Soyeon","family":"Lee","sequence":"first","affiliation":[{"name":"Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu,  Daejeon 305-700, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangjoon","family":"Park","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu,  Daejeon 305-700, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyoil","family":"Chung","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu,  Daejeon 305-700, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Choongho","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Korea University, 2511 Sejong-ro,  Sejong City 339-770, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,6,11]]},"reference":[{"key":"ref_1","unstructured":"Jaclyn, H., Jason, W., and Brian, W. 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Rehabil."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1109\/TNSRE.2011.2120623","article-title":"The integrated virtual environment rehabilitation treadmill system","volume":"19","author":"Feasel","year":"2011","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_14","unstructured":"Minsu, L., Changook, P., Hojin, J., and Jinwoo, S. (2015, January 20\u201323). Use of Multiple Wearable Inertial Sensors in Human Localization. Honolulu, HI, USA."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"333","DOI":"10.3745\/JIPS.2013.9.2.333","article-title":"Adaptive Cross-Device Gait Recognition Using a Mobile Accelerometer","volume":"9","author":"Thang","year":"2013","journal-title":"J. Inf. Process. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/2192-1962-2-18","article-title":"An indoor augmented-reality evacuation system for the Smartphone using personalized Pedometry","volume":"2","author":"Ahn","year":"2012","journal-title":"Hum.-Centric Comput. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.gaitpost.2012.03.033","article-title":"Validity of the Microsoft Kinect for assessment of postural control","volume":"36","author":"Ross","year":"2012","journal-title":"Gait Posture."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/j.apergo.2011.09.011","article-title":"Evaluation of the Kinect\u2122 sensor for 3-D kinematic measurement in the workplace","volume":"43","author":"Tilak","year":"2012","journal-title":"Appl. Ergon."},{"key":"ref_19","unstructured":"Destelle, F., Ahmadi, A., O\u2019Connor, N.E., and Moran, K. (2014, January 1\u20135). Low-Cost accurate skeleton tracking based on fusion of Kinect and wearable inertial sensors. Lisbon, Portugal."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/7\/2\/1043\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:47:47Z","timestamp":1760215667000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/7\/2\/1043"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6,11]]},"references-count":19,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2015,6]]}},"alternative-id":["sym7021043"],"URL":"https:\/\/doi.org\/10.3390\/sym7021043","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2015,6,11]]}}}