{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:06:00Z","timestamp":1760241960932,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,10,29]],"date-time":"2018-10-29T00:00:00Z","timestamp":1540771200000},"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":["U1713206"],"award-info":[{"award-number":["U1713206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Research Plan of Shenzhen","award":["JCYJ20170413112645981, JCYJ20150928162432701 and JCYJ20170811160003571"],"award-info":[{"award-number":["JCYJ20170413112645981, JCYJ20150928162432701 and JCYJ20170811160003571"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a modeling approach to feature classification and environment mapping for indoor mobile robotics via a rotary ultrasonic array and fuzzy modeling. To compensate for the distance error detected by the ultrasonic sensor, a novel feature extraction approach termed \u201cminimum distance of point\u201d (MDP) is proposed to determine the accurate distance and location of target objects. A fuzzy model is established to recognize and classify the features of objects such as flat surfaces, corner, and cylinder. An environmental map is constructed for automated robot navigation based on this fuzzy classification, combined with a cluster algorithm and least-squares fitting. Firstly, the platform of the rotary ultrasonic array is established by using four low-cost ultrasonic sensors and a motor. Fundamental measurements, such as the distance of objects at different rotary angles and with different object materials, are carried out. Secondly, the MDP feature extraction algorithm is proposed to extract precise object locations. Compared with the conventional range of constant distance (RCD) method, the MDP method can compensate for errors in feature location and feature matching. With the data clustering algorithm, a range of ultrasonic distances is attained and used as the input dataset. The fuzzy classification model\u2014including rules regarding data fuzzification, reasoning, and defuzzification\u2014is established to effectively recognize and classify the object feature types. Finally, accurate environment mapping of a service robot, based on MDP and fuzzy modeling of the measurements from the ultrasonic array, is demonstrated. Experimentally, our present approach can realize environment mapping for mobile robotics with the advantages of acceptable accuracy and low cost.<\/jats:p>","DOI":"10.3390\/s18113673","type":"journal-article","created":{"date-parts":[[2018,10,29]],"date-time":"2018-10-29T11:10:41Z","timestamp":1540811441000},"page":"3673","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Feature Extraction and Mapping Construction for Mobile Robot via Ultrasonic MDP and Fuzzy Model"],"prefix":"10.3390","volume":"18","author":[{"given":"Zhili","family":"Long","sequence":"first","affiliation":[{"name":"Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronghua","family":"He","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxiang","family":"He","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1652-9681","authenticated-orcid":false,"given":"Haoyao","family":"Chen","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zuohua","family":"Li","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.1109\/TASE.2017.2731371","article-title":"Toward Socially Aware Robot Navigation in Dynamic and Crowded Environments: A Proactive Social Motion Model","volume":"14","author":"Truong","year":"2017","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s13173-012-0092-4","article-title":"A method to convert floating to fixed-point EKF-SLAM for embedded robotics","volume":"19","author":"Bonato","year":"2013","journal-title":"J. Braz. Comput. Soc."},{"doi-asserted-by":"crossref","unstructured":"Silver, D., Morales, D., Rekleitis, I., Lisien, B., and Choset, H. (May, January 26). Arc carving: Obtaining accurate, low latency maps from ultrasonic range sensors. Proceedings of the 2004 IEEE International Conference on Robotics and Automation (ICRA), New Orleans, LA, USA.","key":"ref_3","DOI":"10.1109\/ROBOT.2004.1308045"},{"unstructured":"Hebert, M. (2000, January 24\u201328). Active and passive range sensing for robotics. Proceedings of the 2000 IEEE International Conference on Robotics and Automation (ICRA), San Francisco, CA, USA.","key":"ref_4"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/S0921-8890(02)00271-3","article-title":"Using infrared sensors for distance measurement in mobile robots","volume":"40","author":"Benet","year":"2002","journal-title":"Robot. Auton. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1017\/S0263574712000732","article-title":"A robust, multi-hypothesis approach to matching occupancy grid maps","volume":"31","author":"Blanco","year":"2013","journal-title":"Robotica"},{"key":"ref_7","first-page":"485","article-title":"Probabilistic Grid Map Based Localizability Estimation for Mobile Robots","volume":"34","author":"Wei","year":"2012","journal-title":"Robots"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s10514-012-9276-1","article-title":"Topological map induction using neighbourhood information of places","volume":"32","author":"Werner","year":"2012","journal-title":"Auton. Robots"},{"unstructured":"Du, Z., Qu, D., Xu, F., and Kai, J. (2010, January 6). Mobile Robot Map Building Based on Ultrasonic Sensors. Proceedings of the National Conference on Access and Processing of Information, Weihai, China.","key":"ref_9"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1109\/70.88147","article-title":"Mobile Robot Localization by Tracking Geometric Beacons","volume":"7","author":"Leonard","year":"2002","journal-title":"IEEE Trans. Robot. Autom."},{"unstructured":"Lee, S.J., Dong, W.C., Wan, K.C., Lim, J.H., and Kang, C.U. (2005, January 2\u20136). Feature based map building using sparse sonar data. Proceedings of the International Conference on Intelligent Robots and Systems, Edmonton, AB, Canada.","key":"ref_11"},{"doi-asserted-by":"crossref","unstructured":"Ismail, H., and Balachandran, B. (2013, January 15\u201321). A Comparison of Feature Extraction Algorithms Based on Sonar Sensor Data. Proceedings of the ASME 2013 International Mechanical Engineering Congress and Exposition, San Diego, CA, USA.","key":"ref_12","DOI":"10.1115\/IMECE2013-62989"},{"doi-asserted-by":"crossref","unstructured":"Heinen, M.R., and Engel, P.M. (2011, January 21\u201324). Incremental feature-based mapping from sonar data using Gaussian mixture models. Proceedings of the ACM Symposium on Applied Computing, TaiChung, Taiwan.","key":"ref_13","DOI":"10.1145\/1982185.1982484"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"6460","DOI":"10.1109\/JSEN.2015.2456900","article-title":"Algorithm Fusion for Feature Extraction and Map Construction from SONAR Data","volume":"15","author":"Ismail","year":"2015","journal-title":"IEEE Sens. J."},{"unstructured":"Lee, S.J., and Song, J.B. (2010, January 18\u201322). A new sonar salient feature structure for EKF-based SLAM. Proceedings of the International Conference on Intelligent Robots and Systems, Taipei, Taiwan.","key":"ref_15"},{"unstructured":"Yuan, S., Huang, L., Zhang, F., Sun, Y., and Huang, K. (July, January 29). A line extraction algorithm for mobile robot using sonar sensor. Proceedings of the 2014 11th World Congress on Intelligent Control and Automation (WCICA), Shenyang, China.","key":"ref_16"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/TRO.2009.2024783","article-title":"Effective Maximum Likelihood Grid Map with Conflict Evaluation Filter Using Sonar Sensors","volume":"25","author":"Lee","year":"2009","journal-title":"IEEE Trans. Robot."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5785","DOI":"10.1109\/TIE.2017.2777411","article-title":"Robust Bearing Angle Error Estimation for Mobile Robots with a Gimballed Ultrasonic Seeker","volume":"65","author":"Suh","year":"2018","journal-title":"IEEE Trans. Ind. Electron."},{"unstructured":"(2018, October 10). Product Introduction. Available online: http:\/\/www.jx-servo.com\/English\/Product\/49513727.html.","key":"ref_19"},{"unstructured":"(2018, October 10). IntoRobot-Atom_Datasheet. Available online: http:\/\/dl.intoyun.com\/terminal\/modules\/datasheets\/en\/IntoRobot-Atom_Datasheet_en.pdf.","key":"ref_20"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1109\/6104.795859","article-title":"Adaptive fuzzy process control of integrated circuit wire bonding","volume":"22","author":"Kinnaird","year":"2002","journal-title":"IEEE Trans. Electron. Packag. Manuf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/j.sna.2011.03.015","article-title":"Fuzzy pattern recognition of impact acoustic signals for nondestructive evaluation","volume":"167","author":"Liu","year":"2011","journal-title":"Sens. Actuators A Phys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1109\/3477.764875","article-title":"Extracting fuzzy control rules from experimental human operator data","volume":"29","author":"Zapata","year":"1999","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1109\/TFUZZ.2015.2501439","article-title":"A Survey of Adaptive Fuzzy Controllers: Nonlinearities and Classifications","volume":"24","author":"Meng","year":"2016","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1109\/TPAMI.2002.1017616","article-title":"An Efficient k-Means Clustering Algorithm: Analysis and Implementation","volume":"24","author":"Kanungo","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/11\/3673\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:26:47Z","timestamp":1760196407000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/11\/3673"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,29]]},"references-count":25,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["s18113673"],"URL":"https:\/\/doi.org\/10.3390\/s18113673","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,10,29]]}}}