Self-localization of an underwater vehicle is particularly challenging due to the absence of Global Positioning System (GPS) reception or features at known positions that could otherwise have been used for position computation. Thus Autonomous Underwater Vehicle (AUV) applications typically require the pre-deployment of a set of beacons. 
This thesis examines the scenario in which the members of a group of AUVs exchange navigation information with one another so as to improve their individual position estimates. 
We describe how the underwater environment poses unique challenges to vehicle navigation not encountered in other environments in which robots operate and how cooperation can improve the performance of self-localization. As intra-vehicle cornmunication is crucial to cooperation, we also address the constraints of the communication channel and the effect that these constraints have on the design of cooperation strategies. 
The classical approaches to underwater self-localization of a single vehicle, as well as more recently developed techniques are presented. We then examine how methods used for cooperating land-vehicles can be transferred to the underwater domain. An algorithm for distributed self-localization, which is designed to take the specific characteristics of the environment into account, is proposed. 
We also address how correlated position estimates of cooperating vehicles can lead to overconfidence in individual position estimates. 
Finally, key to any successful cooperative navigation strategy is the incorporation of the relative positioning between vehicles. The performance of localization algorithms with different geometries is analyzed and a distributed algorithm for the dynamic positioning of vehicles, which serve as dedicated navigation beacons for a fleet of AUVs, is proposed. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

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Cooperative localization for autonomous underwater vehicles

This paper describes an algorithm for distributed acoustic navigation for A utonomous Underwater Vehicles (AUVs). Whereas typical AUV navigation systems utilize pre-calibrated ar rays of static transponders, our work seeks to create a fully mobile network of AUVs that perform acoustic rang ing and data exchange with one another to achieve cooperative positioning for extended duration missions over lar ge areas. The algorithm enumerates possible solutions for the AUV trajectory based on dead-reckoning and range-o ly measurements provided by acoustic modems that are mounted on each vehicle, and chooses the trajectory via minimizatio n of a cost function based on these constraints. The resulting algorithm is computationally efficient, meets the stric t bandwidth requirements of available AUV modems, and has potential to scale well to networks of large numbers of vehicles. The method has undergone extensive experimentation, and results from three different scenario s re reported in this paper, each of which utilizes MIT SCOUT Autonomous Surface Craft (ASC) as convenient platform s for testing. In the first experiment, we utilize three ASCs, each equipped with a Woods Hole acoustic modem, as surrog ates for AUVs. In this scenario, two ASCs serve as Communication/Navigation Aids (CNAs) for a third ASC that compu tes its position based exclusively on GPS positions of the CNAs and acoustic range measurements between platf orms. In the second scenario, an undersea glider is used in conjunction with two ASCs serving as CNAs. Finally, in the third e xperiment, a Bluefin12 AUV serves as the target vehicle. All three experiments demonstrate the succ s ful operation of the technique with real ocean data. Index Terms autonomous underwater vehicles, cooperative navigation, mobile robo tics, sensor networks I. I NTRODUCTION The absence of Global Positioning System (GPS) signals unde rwat r makes navigation for Autonomous Underwater Vehicles (AUVs) a difficult challenge. Without an exte rnal reference in the form of acoustic beacons at known positions, the vehicle has to rely on proprioceptive inform ation obtained through a compass, a Doppler Velocity Logger (DVL) or an Inertial Navigation System (INS) [WYSH00] . Independent of the quality of the sensors used, the error in the position estimate based on dead-reckoning i formation grows without bound. Typical navigation The authors are with the Computer Science and Artificial Intel lig nce Laboratory, Massachusetts Institute of Technolog y, Cambridge, MA 02139, USA October 30, 2008 DRAFT 2 errors are 0.5 % to 2 % of distance traveled for vehicles opera ting within a few hundred meters of the sea floor such that their DVL has a lock on the bottom. Errors as low as 0. 1 % can be obtained with large and expensive INS systems, but for vehicles relying only on a compass and a s peed estimate, errors can be as high as 20 %. By surfacing the AUV can obtain a position update through its GP S, but this is impossible (under ice) or undesirable for many applications. The use of static beacons in the form o f a Long Baseline (LBL) array limits the operation area to a few km and requires a substantial deployment effort before operat ions, especially in deep water. As underwater vehicles become more reliable and affordable the simultaneous use of several AUVs recently became a viable option and multi-vehicle deployments will b ecome standard in the upcoming years. This will not only make possible entirely new types of missions which r ely on cooperation, but will also allow each individual member of the group to benefit from navigation inf ormation obtained from other members. For optimal cooperative localization a few dedicated Communication an d Navigation Aid-AUVs (CNAs), which maintain an accurate estimate of their position through sophisticated DVL and INS sensors, can enable a much larger group of vehicles with less sophisticated navigation suites to main tain an accurate position, as described in [VLCW04a]. The idea of an underwater equivalent to the terrestrial GPS h as long held appeal to AUV researchers. For example, A.C.S.A. has developed a portable undersea tracking range t hat provides a form of “underwater GPS” in a local area [Tho01]. In the A.C.S.A. system, a network of four surfa ce buoys equipped with GPS and RF communications utilize passive acoustic range measurements to track the po sition of a time-synchronized mobile undersea device. While the base system usually employs moored or drifted surfa ce buoys, experiments using self-powered surface craft have also been performed. Further extensions of this c oncept could employ acoustic communications to relay the vehicle pose estimate obtained by the surface buoys back to the undersea vehicle itself. The motivation behind our research is to enable multiple AUV s to cooperatively navigate. The ideal solution would enable heterogeneous teams of AUVs to operate with hig navigational precision, without frequent surfacing for GPS measurements, even for the case when only a small numb er of the AUVs in the team are equipped with expensive inertial sensors. One application of this capabi lity would be to perform rapid, large-area search with a mixed AUV network consisting of Comm/Nav-Aid AUVs, Search -Classify-Map AUVs, and Reacquire-Identify AUVs [VLCW04b]. The problem of cooperative navigation of AUVs is highly inte rconnected to the problem of undersea acoustic communications [Cat90], [KB00], [FJG 01]. Our work capitalizes on recent progress by the Acoustic Modem Group at Woods Hole Oceanographic Institution (WHOI) in deve loping integrated communication and navigation (ranging) capabilities for small AUVs. This application ra ises several interesting challenges for acoustic telemetr y research, such as the need to handle a fully mobile network an d the goal of achieving accurate one-way ranging through stable clock synchronization. There has been a great deal of work in terrestrial settings on the problem of cooperative navigation of multiple mobile robots. Often the problem is cast in terms of a mix of mo bile and static nodes in a large-scale sensor network, with either angle-only or range-only measurement s. A variety of state estimation approaches have been followed, including Markov chain Monte Carlo and set-theor etic state estimators. For example, Liao et al. [LHDS06] October 30, 2008 DRAFT 3 employed a particle filter state estimator for cooperative l oca ization of multiple ground robots using range-only measurements. Djugash et al. [DKSZ06] developed an approach that integrated Simultaneo us Localization and Mapping (SLAM) with mobile sensor networks, achieving self -calibration of a network consisting of mobile and stationary nodes with range measurements. Grocholsky et al. [GSSK06] used nonlinear set-based state estimation techniques for localization of multiple mobile robots with range measurements between platforms. The underwater setting presents some unique challenges for cooperative mobile robotics. The assumption of a fast and reliable communication channel between all parti cipants of the cooperative navigation effort, as made in [RB00], [RDM02], and [MLRT04], does not hold underwater. Due to the strong attenuation of electro-magnetic waves underwater, radio or optical communication is not pra ctic lly feasible except for distances of a few meters. As a result acoustic modems, typically operating between 15 and 30 kHz, provide the only possible means of communicating at long ranges underwater. Data rates are typ ically several orders of magnitude below those achieved with radio-based communication channels [KB00]. With soun d propagation being dependent on temperature and salinity, which can both vary strongly within the water colu mn, the acoustic communication channel is unreliable and its performance hard to predict. This is especially true in shallow water, where severe multi-path is often encountered. The concept of portable landmarks as outlined in [KNH94] is not feasible as it is often difficult for an AUV to hold its position, especially in strong currents. The objective for our work is to develop and test an algorithm for cooperative positioning of multiple mobile undersea vehicles that can use acoustic modems concurrentl y for both ranging and for communication [FJG 01]. The solution must be robust to the errors and time delays that are inherent to acoustic range measurements and must take into account the severe bandwidth constraints of state -of-the-art undersea acoustic modems. This restriction prevents the transfer of full state information between veh icl s. The cooperative navigation problem is complementary to the problems of cooperative motion planning and control for underwater platforms. For example, Leonard et al. have addressed a class of cooperative adaptive sampling problems for networks of AUVs and underwater gliders [LPL 07]. In this work the motion of a fleet of vehicles is directed to acquire optimal data sets based on the predict ions of numerical ocean models. This work typically assumes that accurate navigation information is available , for example through GPS measurements obtained at the surface. This scenario provides a compelling application s cenario in which our cooperative navigation techniques could be applied, obviating the need for all vehicles in the fl e t to surface for positioning. Using a one-way messaging system with the WHOI modem, Eustice et al. [EWSG07] recently implemented a least squares version of a maximum likelihood algorithm to c arry out moving baseline navigation. The approach utilized a particularly accurate heading and dead-reckoni ng system and as well as a specially designed low drift timing clock. II. T ECHNICAL APPROACH In order to cooperate during their mission the AUVs will be ou tfitted with acoustic modems. Data rates on the order of 100 bytes/s over distances of up to 5 km have been a chieved, but given varying channel quality, October 30,

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Cooperative Localization for Autonomous Underwater Vehicles

This document describes the MOOS-IvP autonomy software for unmanned marine vehicles and its use in large-scale ocean sensing systems. MOOS-IvP is composed of two open-source software projects funded by the Office of Naval Research. MOOS provides a core autonomy middleware capability, and the MOOS project additionally provides a set of ubiquitous infrastructure utilities. The IvP Helm is the primary component of an additional set of capabilities implemented to form a full marine autonomy suite known as MOOS-IvP. This software and architecture are platform and mission agnostic and allow for a scalable nesting of unmanned vehicle nodes to form large-scale, long-endurance ocean sensing systems composed of heterogeneous platform types with varying degrees of communications connectivity, bandwidth, and latency. © 2010 Wiley Periodicals, Inc.

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Nested Autonomy for Unmanned Marine Vehicles with MOOS-IvP

A surveillance and guidance method and system for use with autonomously guided, man-on-the-loop or man-in-the-loop guided vehicles where the presence of obstacles must be considered in guiding the vehicle towards a target includes a navigation system configured to determine the position of the vehicle on which it is equipped. A communication system is configured for data exchange between the vehicle, neighboring vehicles and ground stations. A surveillance system is configured to detect and locate fixed or moving targets and obstacles. A computer is configured to track the position of targets and obstacles and to provide guidance commands or 4D flight paths to perform collision avoidance with respect to traffic regulations and procedures, and operational airspace restrictions. Additional computer tasks include station keeping or interception of targets. A command and control system is configured to interact with a user interface and control the vehicle's actuators.

Adaptive surveillance and guidance system for vehicle collision avoidance and interception

An acoustic vector-sensor (also known as vector-hydrophone in underwater applications) is composed of two or three spatially collocated but orthogonally oriented acoustic velocity sensors, plus possibly a collocated acoustic pressure sensor. Such an acoustic vector sensor is versatile for direction-finding, due to its azimuth-elevation spatial response's independence from the incident source's frequency, and bandwidth. However, previously unavailable in the open literature is how the acoustic vector sensor's far-field direction-of-arrival estimates may be adversely affected by any unknown nonideality in the acoustic vector sensor's gain response, phase response, collocation, or orthogonal orientation among its constituent velocity sensors. This paper pioneers a characterization of how these various unknown nonidealities degrade direction-finding accuracy, via Cramer-Rao bound analysis.

CramÉr-Rao Bounds for Direction Finding by an Acoustic Vector Sensor Under Nonideal Gain-Phase Responses, Noncollocation, or Nonorthogonal Orientation

This paper is about the autonomous control of an autonomous underwater vehicle (AUV), and the particular considerations required to allow proper control while towing a 100-meter vector sensor array. Mission related objectives are tempered by the need to consider the effect of a sequence of maneuvers on the motion of the towed array which is thought not to tolerate sharp bends or twists in sensitive material. We describe and motivate an architecture for autonomy structured on the behavior-based control model augmented with a novel approach for performing behavior coordination using multi-objective optimization. We provide detailed in-field experimental results from recent exercises with two 21-inch AUVs in Monterey Bay California.

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D. Battle

Papers

Autonomous Control of an Autonomous Underwater Vehicle Towing a Vector Sensor Array