Uncertainty Modeling for AUV Acquired Bathymetry

Abstract Autonomous Underwater Vehicles (AUVs) are used across a wide range of mission scenarios and from an increasingly diverse set of operators. Use of AUVs for shallow water (less than 200 meters) mapping applications is of increasing interest. However, an update of the total propagated uncertainty TPU model is required to properly attribute bathymetry data acquired from an AUV platform compared with surface platform acquired data. An overview of the parameters that should be considered for data acquired from an AUV platform is discussed. Data acquired in August 2014 using NOAA’s Remote Environmental Measuring UnitS (REMUS) 600 AUV in the vicinity of Portsmouth, NH were processed and analyzed through Leidos’ Survey Analysis and Area Based EditoR (SABER) software. Variability in depth and position of seafloor features observed multiple times from repeat passes of the AUV, and junctioning of the AUV acquired bathymetry with bathymetry acquired from a surface platform are used to evaluate the TPU model and to characterize the AUV acquired data

Integrated Positioning System of Autonomous Underwater Robot and Its Application in High Latitudes of Arctic Zone

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Low cost underwater acoustic localization

Over the course of the last decade, the cost of marine robotic platforms has significantly decreased. In part this has lowered the barriers to entry of exploring and monitoring larger areas of the earth's oceans. However, these advances have been mostly focused on autonomous surface vehicles (ASVs) or shallow water autonomous underwater vehicles (AUVs). One of the main drivers for high cost in the deep water domain is the challenge of localizing such vehicles using acoustics. A low cost one-way travel time underwater ranging system is proposed to assist in localizing deep water submersibles. The system consists of location aware anchor buoys at the surface and underwater nodes. This paper presents a comparison of methods together with details on the physical implementation to allow its integration into a deep sea micro AUV currently in development. Additional simulation results show error reductions by a factor of three.Comment: 73rd Meeting of the Acoustical Society of Americ

AUV SLAM and experiments using a mechanical scanning forward-looking sonar

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

Design and evaluation of an integrated GPS/INS system for shallow-water AUV Navigation

The major problem addressed by this research is the large and/or expensive equipment required by a conventional navigation system to accurately determine the position of an Autonomous Underwater Vehicle (AUV) during all phases of an underwater search or mapping mission. The approach taken was to prototype an integrated navigation system which combines Global Positioning System (OPS) and Inertial Measurement Unit (IMU), waterspeed and heading information using Kalman filtering techniques. Actual implementation was preceded by a computer simulation to test where the unit would fit into a larger hardware and software hierarchy of an AUV. The system was then evaluated in experiments which began with land based cart tests and progressed to open water trials where the unit was placed in a towed body behind a boat and alternately submerged and surfaced to provide periodic OPS updates to the Inertial Navigation System (INS). Test results and qualitative error estimates indicate that submerged navigation accuracy comparable to that of differential OPS may be attainable for periods of 30 seconds or more with low cost components of a small physical size.http://archive.org/details/designndevaluati1094535102NANAU.S. Navy (U.S.N.) authors

Single Transponder Range Only Navigation Geometry (STRONG) applied to REMUS autonomous under water vehicles

Submitted in partial fulfillment of the requirements for Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution August 2005A detailed study was conducted to prove the concept of an iterative approach to single transponder navigation for REMUS Autonomous Underwater Vehicles (AUVs). Although the concept of navigation with one acoustic beacon is not new, the objective was to develop a computer algorithm that could eventually be integrated into the REMUS architecture. This approach uses a least squares fit routine coupled with restrictive geometry and simulated annealing vice Kalman filtering and state vectors. In addition, to provide maximum flexibility, the single transponder was located on a GPS equipped surface ship that was free to move instead of the more common single bottom mounted beacon. Using only a series of spread spectrum ranges logged with time stamp, REMUS standard vehicle data, and reasonable initial conditions, the position at a later time was derived with a figure of merit fit score. Initial investigation was conducted using a noise model developed to simulate the errors suspected with the REMUS sensor suite. Results of this effort were applied to a small at sea test in 3,300 meters with the REMUS 6000 deep water AUV. A more detailed test was executed in Buzzard's Bay, Massachusetts, in 20 meters of water with a REMUS 100 AUV focusing on navigation in a typical search box. While deep water data was too sparse to reveal conclusive results, the Buzzard's Bay work strongly supports the premise that an iterative algorithm can reliably integrate REMUS logged data and an accurate time sequence of ranges to provide position fixes through simple least squares fitting. Ten navigational legs up to1500 meters in length showed that over 90% of the radial position error can be removed from an AUV's position estimate using the STRONG algorithm vice dead reckon navigation with a magnetic compass and Doppler Velocity Log alone (DVL)

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is to the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is to provide a quantitative performance comparison of three estimators: particle filtering (PF), non-linear least-squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.United States. Office of Naval Research (Grant N000140711102)United States. Office of Naval Research. Multidisciplinary University Research InitiativeSingapore. National Research FoundationSingapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Monitorin

Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.Massachusetts Institute of Technology. Department of Mechanical EngineeringSingapore-MIT Alliance for Research and Technology (SMART) (Graduate Fellowship

Typhoon at CommsNet13: Experimental experience on AUV navigation and localization

This paper presents two acoustic-based techniques for Autonomous Underwater Vehicle (AUV) navigation within an underwater network of fixed sensors. The proposed algorithms exploit the positioning measurements provided by an Ultra-Short Base Line (USBL) transducer on-board the vehicle to aid the navigation task. In the considered framework the acoustic measurements are embedded in the communication network scheme, causing time-varying delays in ranging with the fixed nodes. The results presented are obtained with post-processing elaborations of the raw experimental data collected during the CommsNet13 campaign, organized and scientifically led by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE). The experiment involved several research institutions and included among its objectives the evaluation of on-board acoustic USBL systems for navigation and localization of AUVs. The ISME groups of the Universities of Florence and Pisa jointly participated to the experiment with one Typhoon class vehicle. This is a 300 m depth rated AUV with acoustic communication capabilities originally developed by the two groups for archaeological search in the framework of the THESAURUS project. The CommsNet13 Typhoon, equipped with an acoustic modem/USBL head, navigated within the fixed nodes acoustic network deployed by CMRE. This allows the comparison between inertial navigation, acoustic self-localization and ground truth represented by GPS signals (when the vehicle was at the surface)