Efficient and Featureless Approaches to Bathymetric Simultaneous Localisation and Mapping

This thesis investigates efficient forms of Simultaneous Localization and Mapping (SLAM) that do not require explicit identification, tracking or association of map features. The specific application considered here is subsea robotic bathymetric mapping. In this context, SLAM allows a GPS-denied robot operating near the sea floor to create a self-consistent bathymetric map. This is accomplished using a Rao-Blackwellized Particle Filter (RBPF) whereby each particle maintains a hypothesis of the current vehicle state and map that is efficiently maintained using Distributed Particle Mapping. Through particle weighting and resampling, successive observations of the seafloor structure are used to improve the estimated trajectory and resulting map by enforcing map self consistency. The main contributions of this thesis are two novel map representations, either of which can be paired with the RBPF to perform SLAM. The first is a grid-based 2D depth map that is efficiently stored by exploiting redundancies between different maps. The second is a trajectory map representation that, instead of directly storing estimates of seabed depth, records the trajectory of each particle and synchronises it to a common log of bathymetric observations. Upon detecting a loop closure each particle is weighted by matching new observations to the current predictions. For the grid map approach this is done by extracting the predictions stored in the observed cells. For the trajectory map approach predictions are instead generated from a local reconstruction of their map using Gaussian Process Regression. While the former allows for faster map access the latter requires less memory and fully exploits the spatial correlation in the environment, allowing predictions of seabed depth to be generated in areas that were not directly observed previously. In this case particle resampling therefore not only enforces self-consistency in overlapping sections of the map but additionally enforces self-consistency between neighboring map borders. Both approaches are validated using multibeam sonar data collected from several missions of varying scale by a variety of different Unmanned Underwater Vehicles. These trials demonstrate how the corrections provided by both approaches improve the trajectory and map when compared to dead reckoning fused with Ultra Short Baseline or Long Baseline observations. Furthermore, results are compared with a pre-existing state of the art bathymetric SLAM technique, confirming that similar results can be achieved at a fraction of the computation cost. Lastly the added capabilities of the trajectory map are validated using two different bathymetric datasets. These demonstrate how navigation and mapping corrections can still be achieved when only sparse bathymetry is available (e.g. from a four beam Doppler Velocity Log sensor) or in missions where map overlap is minimal or even non-existent

Self consistent bathymetric mapping from robotic vehicles in the deep ocean

Submitted In partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and Woods Hole Oceanographic Institution June 2005Obtaining accurate and repeatable navigation for robotic vehicles in the deep ocean is difficult and consequently a limiting factor when constructing vehicle-based bathymetric maps. This thesis presents a methodology to produce self-consistent maps and simultaneously improve vehicle position estimation by exploiting accurate local navigation and utilizing terrain relative measurements. It is common for errors in the vehicle position estimate to far exceed the errors associated with the acoustic range sensor. This disparity creates inconsistency when an area is imaged multiple times and causes artifacts that distort map integrity. Our technique utilizes small terrain "submaps" that can be pairwise registered and used to additionally constrain the vehicle position estimates in accordance with actual bottom topography. A delayed state Kalman filter is used to incorporate these sub-map registrations as relative position measurements between previously visited vehicle locations. The archiving of previous positions in a filter state vector allows for continual adjustment of the sub-map locations. The terrain registration is accomplished using a two dimensional correlation and a six degree of freedom point cloud alignment method tailored for bathymetric data. The complete bathymetric map is then created from the union of all sub-maps that have been aligned in a consistent manner. Experimental results from the fully automated processing of a multibeam survey over the TAG hydrothermal structure at the Mid-Atlantic ridge are presented to validate the proposed method.This work was funded by the CenSSIS ERC of the Nation Science Foundation under grant EEC-9986821 and in part by the Woods Hole Oceanographic Institution through a grant from the Penzance Foundation

Mapping Complex Marine Environments with Autonomous Surface Craft

This paper presents a novel marine mapping system using an Autonomous Surface Craft (ASC). The platform includes an extensive sensor suite for mapping environments both above and below the water surface. A relatively small hull size and shallow draft permits operation in cluttered and shallow environments. We address the Simultaneous Mapping and Localization (SLAM) problem for concurrent mapping above and below the water in large scale marine environments. Our key algorithmic contributions include: (1) methods to account for degradation of GPS in close proximity to bridges or foliage canopies and (2) scalable systems for management of large volumes of sensor data to allow for consistent online mapping under limited physical memory. Experimental results are presented to demonstrate the approach for mapping selected structures along the Charles River in Boston.United States. Office of Naval Research (N00014-06-10043)United States. Office of Naval Research (N00014-05-10244)United States. Office of Naval Research (N00014-07-11102)Massachusetts Institute of Technology. Sea Grant College Program (grant 2007-R/RCM-20

Underwater inspection using sonar-based volumetric submaps

We propose a submap-based technique for mapping of underwater structures with complex geometries. Our approach relies on the use of probabilistic volumetric techniques to create submaps from multibeam sonar scans, as these offer increased outlier robustness. Special attention is paid to the problem of denoising/enhancing sonar data. Pairwise submap alignment constraints are used in a factor graph framework to correct for navigation drift and improve map accuracy. We provide experimental results obtained from the inspection of the running gear and bulbous bow of a 600-foot, Wright-class supply ship.United States. Office of Naval Research (N00014-12-1-0093)United States. Office of Naval Research (N00014-14-1-0373

Autonomous underwater vehicle navigation and mapping in dynamic, unstructured environments

Thesis (Ph.D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 91-98).This thesis presents a system for automatically building 3-D optical and bathymetric maps of underwater terrain using autonomous robots. The maps that are built improve the state of the art in resolution by an order of magnitude, while fusing bathymetric information from acoustic ranging sensors with visual texture captured by cameras. As part of the mapping process, several internal relationships between sensors are automatically calibrated, including the roll and pitch offsets of the velocity sensor, the attitude offset of the multibeam acoustic ranging sensor, and the full six-degree of freedom offset of the camera. The system uses pose graph optimization to simultaneously solve for the robot's trajectory, the map, and the camera location in the robot's frame, and takes into account the case where the terrain being mapped is drifting and rotating by estimating the orientation of the terrain at each time step in the robot's trajectory. Relative pose constraints are introduced into the pose graph based on multibeam submap matching using depth image correlation, while landmark-based constraints are used in the graph where visual features are available. The two types of constraints work in concert in a single optimization, fusing information from both types of mapping sensors and yielding a texture-mapped 3-D mesh for visualization. The optimization framework also allows for the straightforward introduction of constraints provided by the particular suite of sensors available, so that the navigation and mapping system presented works under a variety of deployment scenarios, including the potential incorporation of external localization systems such as long-baseline acoustic networks. Results of using the system to map the draft of rotating Antarctic ice floes are presented, as are results fusing optical and range data of a coral reef.by Clayton Gregory Kunz.Ph.D

Review : Bathymetry Mapping Using Underwater Acoustic Technology

The bathymetry mapping using underwater acoustic technology very important in Indonesia waters. Bathymetry is the result of measuring the height of the seabed so that the bathymetric map provides information about the seabed, where this information can provide benefits to several fields related to the seabed. In bathymetry mapping uses underwater acoustic technology where among them is using Single beam echosounder and MBES (Multibeam Echosounder System), and multibeam echosounder (MBES) is acoustic equipment that is intensively used frequently in basic waters mapping. The advantage of using underwater acoustic technology is the acquisition and processing of data in real time, high accuracy and precision (correction of the bathymetry data was carried out with reference to the 2008 International Hydrographic Organization (IHO), and cannot be a threat or damage to objects. Retrieval of bathymetry data must use parallel patterns, namely: patterns with perpendicular sounding directions and tend to be parallel to longitudinal lines or in accordance with parallel sounding patterns

Coverage Path Planning with Real‐time Replanning and Surface Reconstruction for Inspection of Three‐dimensional Underwater Structures using Autonomous Underwater Vehicles

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113717/1/rob21554.pd

Submeter bathymetric mapping of volcanic and hydrothermal features on the East Pacific Rise crest at 9°50′N

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 8 (2007): Q01006, doi:10.1029/2006GC001333.Recent advances in underwater vehicle navigation and sonar technology now permit detailed mapping of complex seafloor bathymetry found at mid-ocean ridge crests. Imagenex 881 (675 kHz) scanning sonar data collected during low-altitude (~5 m) surveys conducted with DSV Alvin were used to produce submeter resolution bathymetric maps of five hydrothermal vent areas at the East Pacific Rise (EPR) Ridge2000 Integrated Study Site (9°50′N, “bull's-eye”). Data were collected during 29 dives in 2004 and 2005 and were merged through a grid rectification technique to create high-resolution (0.5 m grid) composite maps. These are the first submeter bathymetric maps generated with a scanning sonar mounted on Alvin. The composite maps can be used to quantify the dimensions of meter-scale volcanic and hydrothermal features within the EPR axial summit trough (AST) including hydrothermal vent structures, lava pillars, collapse areas, the trough walls, and primary volcanic fissures. Existing Autonomous Benthic Explorer (ABE) bathymetry data (675 kHz scanning sonar) collected at this site provide the broader geologic context necessary to interpret the meter-scale features resolved in the composite maps. The grid rectification technique we employed can be used to optimize vehicle time by permitting the creation of high-resolution bathymetry maps from data collected during multiple, coordinated, short-duration surveys after primary dive objectives are met. This method can also be used to colocate future near-bottom sonar data sets within the high-resolution composite maps, enabling quantification of bathymetric changes associated with active volcanic, hydrothermal and tectonic processes.This work was supported by an NSF Ridge2000 fellowship to V.L.F. and a Woods Hole Oceanographic Institution fellowship supported by the W. Alan Clark Senior Scientist Chair (D.J.F.). Funding was also provided by the Censsis Engineering Research Center of the National Science Foundation under grant EEC-9986821. Support for field and laboratory studies was provided by the National Science Foundation under grants OCE-9819261 (D.J.F. and M.T.), OCE-0096468 (D.J.F. and T.S.), OCE-0328117 (SMC), OCE-0525863 (D.J.F. and S.A.S.), OCE-0112737 ATM-0427220 (L.L.W.), and OCE- 0327261 and OCE-0328117 (T.S.). Additional support was provided by The Edwin Link Foundation (J.C.K.)