TY - GEN
T1 - Accurate localization with COAG features and self-adaptive energy region
AU - Kim, Dong Il
AU - Song, Jae Bok
N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Localization is very important for autonomous navigation of a mobile robot. For outdoor localization, Monte Carlo Localization (MCL) is used with the digital surface model. In order to develop an improved localization technique, in this study, commonly observed from air and ground (COAG) features are incorporated into an MCL localization system by means of an energy function to determine candidates. Experiments in real environments show improved localization accuracy over methods using MCL with COAG features.
AB - Localization is very important for autonomous navigation of a mobile robot. For outdoor localization, Monte Carlo Localization (MCL) is used with the digital surface model. In order to develop an improved localization technique, in this study, commonly observed from air and ground (COAG) features are incorporated into an MCL localization system by means of an energy function to determine candidates. Experiments in real environments show improved localization accuracy over methods using MCL with COAG features.
KW - MCL
KW - Monte Carlo Localization
UR - http://www.scopus.com/inward/record.url?scp=84884884761&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84884884761&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40852-6_58
DO - 10.1007/978-3-642-40852-6_58
M3 - Conference contribution
AN - SCOPUS:84884884761
SN - 9783642408519
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 576
EP - 583
BT - Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings
PB - Springer Verlag
T2 - 6th International Conference on Intelligent Robotics and Applications, ICIRA 2013
Y2 - 25 September 2013 through 28 September 2013
ER -