{"_id":"5FDANWFcZyAMBXhwL","bibbaseid":"antonelli-chiaverim-fusco-excitingtrajectoriesformobilerobotodometrycalibration-2003","authorIDs":[],"author_short":["Antonelli, G.","Chiaverim, S.","Fusco, G."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Antonelli"],"firstnames":["Gianluca"],"suffixes":[]},{"propositions":[],"lastnames":["Chiaverim"],"firstnames":["Stefano"],"suffixes":[]},{"propositions":[],"lastnames":["Fusco"],"firstnames":["Giuseppe"],"suffixes":[]}],"title":"Exciting trajectories for mobile robot odometry calibration","booktitle":"IFAC Proceedings Volumes (IFAC-PapersOnline)","volume":"36","number":"17","doi":"10.1016/S1474-6670(17)33422-5","issn":"ISSN(print='14746670', electronic=None)","abstract":"Copyright © IFAC Robot Control, Wrocław, Poland, 2003.Odometry calibration is the identification of a set of model parameters that allows to estimate the vehicle position/orientation starting from wheels' encoders measurements. Usually the calibration is achieved using measurements obtained by trial-and-error or heuristic trajectories; these approaches may eventually lead to ill-conditioned numerical problems. In this paper, a least-squares methods is proposed and the optimality of the measurement set is evaluated. Experimental results confirm the efficiency of the algorithm developed.","year":"2003","bibtex":"@inproceedings{Antonelli2003f,\n author = {Antonelli, Gianluca and Chiaverim, Stefano and Fusco, Giuseppe},\n title = {Exciting trajectories for mobile robot odometry calibration},\n booktitle = {IFAC Proceedings Volumes (IFAC-PapersOnline)},\n volume = {36},\n number = {17},\n doi = {10.1016/S1474-6670(17)33422-5},\n issn = {ISSN(print='14746670', electronic=None)},\n abstract = {Copyright © IFAC Robot Control, Wrocław, Poland, 2003.Odometry calibration is the identification of a set of model parameters that allows to estimate the vehicle position/orientation starting from wheels' encoders measurements. Usually the calibration is achieved using measurements obtained by trial-and-error or heuristic trajectories; these approaches may eventually lead to ill-conditioned numerical problems. In this paper, a least-squares methods is proposed and the optimality of the measurement set is evaluated. Experimental results confirm the efficiency of the algorithm developed.},\n year = {2003},\n}\n\n","author_short":["Antonelli, G.","Chiaverim, S.","Fusco, G."],"key":"Antonelli2003f","id":"Antonelli2003f","bibbaseid":"antonelli-chiaverim-fusco-excitingtrajectoriesformobilerobotodometrycalibration-2003","role":"author","urls":{},"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://bibbase.org/network/files/okun7dwBAcdJr9Pjf","creationDate":"2020-11-20T18:08:15.227Z","downloads":0,"keywords":[],"search_terms":["exciting","trajectories","mobile","robot","odometry","calibration","antonelli","chiaverim","fusco"],"title":"Exciting trajectories for mobile robot odometry calibration","year":2003,"dataSources":["tmWCYeuhcvDf3RtcE","TEXnJtjg2N8LiJXTo","FSPYopyGjCq7Y7DYR","z3HQC4e84dBiezoGD","p9R77an3vBgkDdbZo","KNwMR327jkTSCivPb","WjpYhzMSpr7LSfxSN","2pvNPsE6yJzsbk74s","eFrCR4PYs4J9ZrHjt","ij6Z4HQTWDPBgDgEB","BMiF4XZ8BddcYmbYN","LYsdTrM6sSKfnGPrC","SeTjrFSn38FEagCDn","ou5bJ5rQojNquKTfQ","XpfhSYxep2nHiHnHx","9AdYtRjQALwZoyq3T","DaS4ALDSRNJJaKDP5","aDwHjqvhLWojw85rJ","AFYCvMMrmkLN3ZsvR"]}