{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:24:22Z","timestamp":1760239462583,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T00:00:00Z","timestamp":1605484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61903353"],"award-info":[{"award-number":["61903353"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SINOPEC Programmes for Science and Technology Development","award":["PE19008-8"],"award-info":[{"award-number":["PE19008-8"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["WK2100000013"],"award-info":[{"award-number":["WK2100000013"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The accurate terrain classification in real time is of great importance to an autonomous robot working in field, because the robot could avoid non-geometric hazards, adjust control scheme, or improve localization accuracy, with the aid of terrain classification. In this paper, we investigate the vibration-based terrain classification (VTC) in a dynamic environment, and propose a novel learning framework, named DyVTC, which tackles online-collected unlabeled data with concept drift. In the DyVTC framework, the exterior disagreement (ex-disagreement) and interior disagreement (in-disagreement) are proposed novely based on the feature diversity and intrinsic temporal correlation, respectively. Such a disagreement mechanism is utilized to design a pseudo-labeling algorithm, which shows its compelling advantages in extracting key samples and labeling; and consequently, the classification accuracy could be retrieved by incremental learning in a changing environment. Since two sets of features are extracted from frequency and time domain to generate disagreements, we also name the proposed method feature-temporal disagreement adaptation (FTDA). The real-world experiment shows that the proposed DyVTC could reach an accuracy of 89.5%, but the traditional time- and frequency-domain terrain classification methods could only reach 48.8% and 71.5%, respectively, in a dynamic environment.<\/jats:p>","DOI":"10.3390\/s20226550","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T21:48:52Z","timestamp":1605563332000},"page":"6550","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Frequency-Temporal Disagreement Adaptation for Robotic Terrain Classification via Vibration in a Dynamic Environment"],"prefix":"10.3390","volume":"20","author":[{"given":"Chen","family":"Cheng","sequence":"first","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei 230027, China"},{"name":"School of Information Engineering, Anhui Institute of International Business, Hefei 231131, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ji","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei 230027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7583-0944","authenticated-orcid":false,"given":"Wenjun","family":"Lv","sequence":"additional","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei 230027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4407-1412","authenticated-orcid":false,"given":"Yuping","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei 230027, China"},{"name":"Department of Research and Development, Anhui Etown Information Technology Co., Ltd, Hefei 230011, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zerui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei 230027, China"},{"name":"Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenhui","family":"Yuan","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China"},{"name":"School of Computer Science and Technology, Anhui University, Hefei 230601, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saifei","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China"},{"name":"School of Computer Science and Technology, Anhui University, Hefei 230601, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11221","DOI":"10.3390\/s120811221","article-title":"Complete scene recovery and terrain classification in textured terrain meshes","volume":"12","author":"Song","year":"2012","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"785","DOI":"10.3390\/s130100785","article-title":"Cross-coupled control for all-terrain rovers","volume":"13","author":"Reina","year":"2013","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Reinstein, M., Kubelka, V., and Zimmermann, K. 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