Contributions to automated realtime underwater navigation

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2012This dissertation presents three separate–but related–contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field–some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current–the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework–without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation.I have been financially supported by: the National Defense Science and Engineering Graduate (NDSEG) Fellowship administered by the American Society for Engineering Education, the Edwin A. Link Foundation Ocean Engineering and Instrumentation Fellowship, and WHOI Academic Programs office

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

Design considerations for engineering autonomous underwater vehicles

Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2007Autonomous Underwater Vehicles (AUVs) have been established as a viable tool for Oceanographic Sciences. Being untethered and independent, AUVs fill the gap in Ocean Exploration left by the existing manned submersible and remotely operated vehicles (ROV) technology. AUVs are attractive as cheaper and efficient alternatives to the older technologies and are breaking new ground in many applications. Designing an autonomous vehicle to work in the harsh environment of the deep ocean comes with its set of challenges. This paper discusses how the current engineering technologies can be adapted to the design of AUVs. Recently, as the AUV technology has matured, we see AUVs being used in a variety of applications ranging from sub-surface sensing to sea-floor mapping. The design of the AUV, with its tight constraints, is very sensitive to the target application. Keeping this in mind, the goal of this thesis is to understand how some of the major issues affect the design of the AUV. This paper also addresses the mechanical and materials issues, power system design, computer architecture, navigation and communication systems, sensor considerations and long term docking aspects that affect AUV design. With time, as the engineering sciences progress, the AUV design will have to change in order to optimize its performance. Thus, the fundamental issues discussed in this paper can assist in meeting the challenge of maintaining AUV design on par with modern technology.This work was funded by the NSF Center for Subsurface Sensing and Imaging Systems (CenSSIS) Engineering Research Center (ENC) grant no. EEC-99868321

Estimation filtering for Deep Water Navigation

The navigation task for Unmanned Underwater Vehicles is made difficult in a deep water scenario because of the lack of bottom lock for Doppler Velocity Log (DVL). This is due to the operating altitude that, for this kind of applications, is typically greater than the sensor maximum range. The effect is that the velocity measurements are biased by sea currents resulting in a rapidly increasing estimation error drift. The solution proposed in this work is based on a distributed, cooperative strategy strongly relying on an acoustic underwater network. According to the distributed philosophy, an instance of a specifically designed navigation filter (named DWNF - Deep Water Navigation Filter) is executed by each vehicle. Each DWNF relies on different Extended Kalman Filters (EKFs) running in parallel on-board: one for own navigation state estimation (AUV-EKF), the other ones for the navigation state of the remaining assets (Asset-EKF). The AUV-EKF is designed to simultaneously estimate the vehicle position and the sea current for more reliable predictions. The DWNF builds in real-time a database of past measurements and estimations; in this way it can correctly deal with delayed information. An outlier detection and rejection policy based on the Mahalanobis distance associated to each measurement is implemented. The experimental validation of the proposed approach took place in a deep water scenario during the Dynamic Mongoose’17 exercise off the South coast of Iceland (June-July 2017); preliminary analysis of the results is presented

Mid-water current aided localization for autonomous underwater vehicles

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Autonomous Robots 40 (2016): 1207–1227, doi:10.1007/s10514-016-9547-3.Survey-class Autonomous Underwater Vehi- cles (AUVs) typically rely on Doppler Velocity Logs (DVL) for precision localization near the seafloor. In cases where the seafloor depth is greater than the DVL bottom-lock range, localizing between the surface and the seafloor presents a localization problem since both GPS and DVL observations are unavailable in the mid- water column. This work proposes a solution to this problem that exploits the fact that current profile layers of the water column are near constant over short time scales (in the scale of minutes). Using observations of these currents obtained with the Acoustic Doppler Cur- rent Profiler (ADCP) mode of the DVL during descent, along with data from other sensors, the method dis- cussed herein constrains position error. The method is validated using field data from the Sirius AUV coupled with view-based Simultaneous Localization and Map- ping (SLAM) and on descents up to 3km deep with the Sentry AUV.This work is supported in part by NCRIS IMOS, the Australian Research Council (ARC), the New South Wales Government and the Woods Hole Oceanographic Institution.2017-02-1

CES-515 Towards Localization and Mapping of Autonomous Underwater Vehicles: A Survey

Autonomous Underwater Vehicles (AUVs) have been used for a huge number of tasks ranging from commercial, military and research areas etc, while the fundamental function of a successful AUV is its localization and mapping ability. This report aims to review the relevant elements of localization and mapping for AUVs. First, a brief introduction of the concept and the historical development of AUVs is given; then a relatively detailed description of the sensor system used for AUV navigation is provided. As the main part of the report, a comprehensive investigation of the simultaneous localization and mapping (SLAM) for AUVs are conducted, including its application examples. Finally a brief conclusion is summarized

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

Design considerations for engineering AUVs

Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2007.Includes bibliographical references (p. 85-89).Autonomous Underwater Vehicles (AUVs) have been established as a viable tool for Oceanographic Sciences. Being untethered and independent, AUVs fill the gap in Ocean Exploration left by the existing manned submersible and remotely operated vehicles (ROV) technology. AUVs are attractive as cheaper and efficient alternatives to the older technologies and are breaking new ground in many applications. Designing an autonomous vehicle to work in the harsh environment of the deep ocean comes with its set of challenges. This paper discusses how the current engineering technologies can be adapted to the design of AUVs. Recently, as the AUV technology has matured, we see AUVs being used in a variety of applications ranging from sub-surface sensing to sea-floor mapping. The design of the AUV, with its tight constraints, is very sensitive to the target application. Keeping this in mind, the goal of this thesis is to understand how some of the major issues affect the design of the AUV. This paper also addresses the mechanical and materials issues, power system design, computer architecture, navigation and communication systems, sensor considerations and long term docking aspects that affect AUV design. With time, as the engineering sciences progress, the AUV design will have to change in order to optimize its performance. Thus, the fundamental issues discussed in this paper can assist in meeting the challenge of maintaining AUV design on par with modern technology.by Vikrant P. Shah.S.M

Optimization of the Geometry of Communication for Autonomous Missions of Underwater Vehicles

The potential of Autonomous Underwater Vehicles (AUVs) working as a team in sampling, monitoring and surveillance of the marine environment has been realized since quite a long time. One of the most relevant obstacle to their operational implementation resides in the limitations of the acoustic channel for inter-vehicle communications. Underwater acoustic modeling and simulation plays an important role in predicting possible losses and transmission failures between them, and underwater sound propagation can be precisely measured or estimated. In this thesis, sound speed data from a real experiment (CommsNet13) were used to simulate environmental conditions and analyze acoustic communication between an USBL-vehicle on the sea surface and an acoustic modem on the sea bottom, in order achieve an effective geometry of transmission for future trials

RRS Discovery Cruise DY108‐109, 6 Sept - 2 Oct 2019. CLASS – Climate‐linked Atlantic System Science Darwin Mounds Marine Protected Area habitat monitoring, BioCAM ‐ first equipment trials. BLT‐ Recipes: pilot study

DY108/109 was a combined expedition, integrating a series of scientific and technological objectives related to three different projects. The main study area was the Darwin Mounds Marine Protected Area, an area of small cold‐water coral mounds in the Northern Rockall Trough, discovered by NOC scientists in 1998 and protected from bottom contact fisheries (mainly bottom trawling) since 2003. As part of the NERC CLASS programme (Climate‐Linked Atlantic Sector Science), the aim was to assess the status of the coral mounds, in order to identify and quantify any long‐term changes to this deep‐sea habitat. The mounds were surveyed with the Autosub6000 AUV (sidescan sonar), the HyBIS video platform and a series of targeted boxcores, repeating a first round of monitoring efforts undertaken in 2011 (expedition JC060). In addition, two settlement experiments deployed in 2011 were recovered on board. The second aim of the cruise was to demonstrate and test the latest innovation in survey technology as a potential new method for monitoring this type of seafloor habitat. The new BioCam system, a combined stereo camera and double laser line scanner integrated in the Autosub6000, was developed under the NERC Oceanids Marine Sensor Capital programme. BioCam enabled millimetre‐resolution 3D colour reconstructions of the seabed over areas that are an order of magnitude larger than typically covered with conventional visual methods (~30ha/day). This type of technology will revolutionise marine habitat monitoring in the future, both in terms of area covered and level of information obtained. In addition to these habitat mapping and monitoring activities in the Darwin Mound area, DY108/109 also supported two oceanographic studies of the Rockall Trough. For the NERC‐funded project BLT‐Recipes, two 24h CTD stations were occupied on the Irish margin, as pilot study to support further work in 2020 and 2021. For the oceanographic part of the CLASS programme, a number of single CTD casts were taken along the “Ellett Line”, while the turn‐around of a lander with upward‐looking ADCP was attempted. Unfortunately, investigation with the HyBIS platform confirmed that the lander was severely damaged and could not be recovered. Despite some time lost to weather and unfortunate equipment malfunctioning, the expedition was a success, with 10 HyBIS dives completed (76h seabed video), two sidescan sonar surveys repeated, 20 successful boxcores taken, sieved an analysed on board, one mooring deployed and 48 CTD casts completed. Most of all, the BioCam system performed excellently, staightaway from its first deployment, and acquired two dense grid survey datasets covering ~60ha in total. KEYWORDS Cold‐water coral, BioCam, CLASS, Marine Protected Area, Darwin Mounds, monitoring, habitat mapping, Autosub6000, AUV, Rockall Trough, Ellett Line, OSNAP, turbulent mixin