title: AUV SLAM and experiments using a mechanical scanning forward-looking sonar.
abstract: Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods.
authors.affiliation: School of Information Science and Engineering, Ocean University of China, 238 Songling Road, Qingdao 266100, China. bhe@ouc.edu.cn
authors.forename: Bo
authors.initials: B
authors.lastname: He
authors.forename: Yan
authors.initials: Y
authors.lastname: Liang
authors.forename: Xiao
authors.initials: X
authors.lastname: Feng
authors.forename: Rui
authors.initials: R
authors.lastname: Nian
authors.forename: Tianhong
authors.initials: T
authors.lastname: Yan
authors.forename: Minghui
authors.initials: M
authors.lastname: Li
authors.forename: Shujing
authors.initials: S
authors.lastname: Zhang