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Based on the motion control method and double evolutionary probability neural network, the abnormal motion signal is detected by fuzzy weighting method and fuzzy matching. Experimental results show that the method can effectively solve the problem of high false alarm rate and false positive rate, and promote the development of robot motion signal anomaly detection technology.<\/jats:p>","DOI":"10.3233\/jcm-226414","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T11:30:41Z","timestamp":1662118241000},"page":"1955-1966","source":"Crossref","is-referenced-by-count":0,"title":["Abnormal motion signal detection of mobile robot based on deep learning"],"prefix":"10.1177","volume":"22","author":[{"given":"Hongxia","family":"Zhang","sequence":"first","affiliation":[]}],"member":"179","reference":[{"key":"10.3233\/JCM-226414_ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3077631"},{"issue":"6","key":"10.3233\/JCM-226414_ref2","doi-asserted-by":"crossref","first-page":"115454","DOI":"10.1016\/j.eswa.2021.115454","article-title":"A novel inertia moment estimation algorithm collaborated with active force control 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