TY - GEN
T1 - A localization method using a dynamical model and an extended Kalman filtering for X4-AUV
AU - Watanabe, Keigo
AU - Yamaguchi, Takanori
AU - Nagai, Isaku
PY - 2017
Y1 - 2017
N2 - The self-position estimation problem of X4-AUV, which is an autonomous underwater vehicle (AUV) driven by four thrusters, is considered. Since a self-position cannot be underwater measured directly using GPS etc., we have to consider any method for realizing it by an indirect method. The AUV treated by this research has a mechanical structure that a self-position is controlled by changing the attitude from the feature of drive mechanism, and it can observe an attitude angle from an internal sensor, so that based on the dynamical model of the present AUV, a method for estimating the self-position is proposed by applying an extended Kalman filter. The usefulness of this technique is demonstrated by checking the feasibility in the simulation of the position control that used the position estimate.
AB - The self-position estimation problem of X4-AUV, which is an autonomous underwater vehicle (AUV) driven by four thrusters, is considered. Since a self-position cannot be underwater measured directly using GPS etc., we have to consider any method for realizing it by an indirect method. The AUV treated by this research has a mechanical structure that a self-position is controlled by changing the attitude from the feature of drive mechanism, and it can observe an attitude angle from an internal sensor, so that based on the dynamical model of the present AUV, a method for estimating the self-position is proposed by applying an extended Kalman filter. The usefulness of this technique is demonstrated by checking the feasibility in the simulation of the position control that used the position estimate.
KW - Extended kalman filter
KW - Localization
KW - Nonholonomic control
KW - X4-AUV
UR - http://www.scopus.com/inward/record.url?scp=85028469725&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028469725&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-65289-4_77
DO - 10.1007/978-3-319-65289-4_77
M3 - Conference contribution
AN - SCOPUS:85028469725
SN - 9783319652887
VL - 10462 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 834
EP - 845
BT - Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings
PB - Springer Verlag
T2 - 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017
Y2 - 16 August 2017 through 18 August 2017
ER -