TY - GEN
T1 - Underwater localization and 3D mapping of submerged structures with a single-beam scanning sonar
AU - Wang, Jinkun
AU - Bai, Shi
AU - Englot, Brendan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/21
Y1 - 2017/7/21
N2 - We present a novel approach to perform underwater simultaneous localization and mapping (SLAM) using a small inspection-class remotely operated vehicle (ROV) equipped with a single-beam scanning sonar, amidst high levels of noise present in the sonar data, and in the absence of inertial/odometry measurements. Features are extracted from hierarchically grouped clusters of sonar returns, data association is performed via the iterative joint compatibility test, and the vehicle's trajectory and map are estimated using incremental smoothing and mapping (iSAM). The resulting point clouds derived from the ROV's sonar are used to produce Gaussian process occupancy maps, which interpolate among gaps in the acoustic range data to produce descriptive 3D maps of submerged structures. The proposed localization and mapping approach is demonstrated using data gathered in two harbor environments in close proximity to piers and seawalls.
AB - We present a novel approach to perform underwater simultaneous localization and mapping (SLAM) using a small inspection-class remotely operated vehicle (ROV) equipped with a single-beam scanning sonar, amidst high levels of noise present in the sonar data, and in the absence of inertial/odometry measurements. Features are extracted from hierarchically grouped clusters of sonar returns, data association is performed via the iterative joint compatibility test, and the vehicle's trajectory and map are estimated using incremental smoothing and mapping (iSAM). The resulting point clouds derived from the ROV's sonar are used to produce Gaussian process occupancy maps, which interpolate among gaps in the acoustic range data to produce descriptive 3D maps of submerged structures. The proposed localization and mapping approach is demonstrated using data gathered in two harbor environments in close proximity to piers and seawalls.
UR - http://www.scopus.com/inward/record.url?scp=85027981670&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85027981670&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2017.7989567
DO - 10.1109/ICRA.2017.7989567
M3 - Conference contribution
AN - SCOPUS:85027981670
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 4898
EP - 4905
BT - ICRA 2017 - IEEE International Conference on Robotics and Automation
T2 - 2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Y2 - 29 May 2017 through 3 June 2017
ER -