{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:30:21Z","timestamp":1760243421169,"version":"build-2065373602"},"reference-count":13,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2013,1,24]],"date-time":"2013-01-24T00:00:00Z","timestamp":1358985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The possibility to identify with significant accuracy the position of a vehicle in a mapping reference frame for driving directions and best-route analysis is a topic which is attracting a lot of interest from the research and development sector. To reach the objective of accurate vehicle positioning and integrate response events, it is necessary to estimate position, orientation and velocity of the system with high measurement rates. In this work we test a system which uses low-cost sensors, based on Micro Electro-Mechanical Systems (MEMS) technology, coupled with information derived from a video camera placed on a two-wheel motor vehicle (scooter). In comparison to a four-wheel vehicle; the dynamics of a two-wheel vehicle feature a higher level of complexity given that more degrees of freedom must be taken into account. For example a motorcycle can twist sideways; thus generating a roll angle. A slight pitch angle has to be considered as well; since wheel suspensions have a higher degree of motion compared to four-wheel motor vehicles. In this paper we present a method for the accurate reconstruction of the trajectory of a \u201cVespa\u201d scooter; which can be used as alternative to the \u201cclassical\u201d approach based on GPS\/INS sensor integration. Position and orientation of the scooter are obtained by integrating MEMS-based orientation sensor data with digital images through a cascade of a Kalman filter and a Bayesian particle filter.<\/jats:p>","DOI":"10.3390\/s130201510","type":"journal-article","created":{"date-parts":[[2013,1,24]],"date-time":"2013-01-24T11:29:13Z","timestamp":1359026953000},"page":"1510-1522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Low-Cost MEMS Sensors and Vision System for Motion and Position Estimation of a Scooter"],"prefix":"10.3390","volume":"13","author":[{"given":"Alberto","family":"Guarnieri","sequence":"first","affiliation":[{"name":"CIRGEO, Interdepartment Research Center for Geomatics, University of Padova, viale dell'Universit\u00e0 16, 35020 Legnaro, Padova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4796-6406","authenticated-orcid":false,"given":"Francesco","family":"Pirotti","sequence":"additional","affiliation":[{"name":"CIRGEO, Interdepartment Research Center for Geomatics, University of Padova, viale dell'Universit\u00e0 16, 35020 Legnaro, Padova, Italy"}]},{"given":"Antonio","family":"Vettore","sequence":"additional","affiliation":[{"name":"CIRGEO, Interdepartment Research Center for Geomatics, University of Padova, viale dell'Universit\u00e0 16, 35020 Legnaro, Padova, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2013,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"638","DOI":"10.3390\/s110100638","article-title":"Sensing Movement: Microsensors for Body Motion Measurement","volume":"11","author":"Zeng","year":"2011","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7606","DOI":"10.3390\/s110807606","article-title":"Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range","volume":"11","author":"Girard","year":"2011","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1109\/TAES.2002.1008998","article-title":"Direct Kalman Filtering Approach for GPS\/INS Integration","volume":"38","author":"Qi","year":"2002","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_4","unstructured":"El-Sheimy, N., and Schwarz, K. Integrating Differential GPS Receivers with an INS and CCD Cameras for Mobile GIS Data Collection. Ottawa, ON, Canada."},{"key":"ref_5","unstructured":"Barbarella, M., Gandolfi, S., Meffe, A., and Burchi, A. (2011, January 13\u201316). A Test Field for Mobile Mapping System: Design, Set up and First Test Results. Cracow, Poland."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Piras, M., Cina, A., and Lingua, A. (2008, January 5\u20136). Low Cost Mobile Mapping Systems: An Italian Experience. Monterey, CA, USA.","DOI":"10.1109\/PLANS.2008.4570077"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s12518-011-0069-6","article-title":"GIMPHI: A New Integration Approach for Early Impact Assessment","volume":"3","author":"Lingua","year":"2011","journal-title":"Appl. Geomatics"},{"key":"ref_8","first-page":"312","article-title":"The Stability of the Motion of a Bicycle","volume":"30","author":"Whipple","year":"1899","journal-title":"Quarterly J. Pure Appl. Math."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/MCS.2006.1700044","article-title":"Bicycles, Motorcycles and Models","volume":"26","author":"Limebeer","year":"2006","journal-title":"IEEE Control Syst. Mag."},{"key":"ref_10","unstructured":"Frezza, R., and Vettore, A. (2001, January 3\u20135). Motion Estimation by Vision for Mobile Mapping with a Motorcycle. Cairo, Egypt."},{"key":"ref_11","unstructured":"Nori, F., and Frezza, R. (2003, January 9\u201311). Accurate Reconstruction of the Path Followed by a Motorcycle from on Board Camera Images. Columbus, OH, USA."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/361237.361242","article-title":"Use of the Hough Transformation to Detect Lines and Curves in Pictures","volume":"15","author":"Duda","year":"1972","journal-title":"Commun. ACM"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1109\/78.978396","article-title":"Particle Filters for Positioning, Navigation and Tracking","volume":"50","author":"Gustafsson","year":"2001","journal-title":"IEEE Trans. Signal Process"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/2\/1510\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:44:31Z","timestamp":1760219071000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/2\/1510"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,24]]},"references-count":13,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2013,2]]}},"alternative-id":["s130201510"],"URL":"https:\/\/doi.org\/10.3390\/s130201510","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2013,1,24]]}}}