A complete solution to underwater navigation in the presence of unknown currents based on range measurements from a single location

Gadre, A.S.; Stilwell, Daniel J.

doi:10.1109/iros.2005.1545230

Cited by 95 publications

(35 citation statements)

References 6 publications

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“…Stilwell and colleagues [24], [14], [13] have implemented a system in which an AUV can localize itself by using a single ranging beacon at known position while also measuring the water current.…”

mentioning

confidence: 99%

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Fallon

Παπαδόπουλος

Leonard

et al. 2010

The International Journal of Robotics Research

191

126

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This paper describes 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 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 provide a quantitative performance comparison of three estimators: particle filtering (PF), Nonlinear 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.

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mentioning

confidence: 99%

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Fallon

Παπαδόπουλος

Leonard

et al. 2010

The International Journal of Robotics Research

191

126

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“…This section reviews some of the references most relevant to this paper. Navigation with a single, fixed beacon whose position is known a priori has been reported using several different estimation techniques-a least squares approach in [21] and [1], and a vehicle-based extended Kalman filter (EKF) in [16] and [10]. Navigation with respect to a moving beacon whose position is not known a priori is reported in [17] using a nonlinear least mean square method; in [6] using a maximum likelihood method; and in [27] using a centralized EKF.…”

Section: Single-beacon Navigationmentioning

confidence: 99%

Advances in decentralized single-beacon acoustic navigation for underwater vehicles: Theory and simulation

Webster

Whitcomb

Eustice

2010

2010 IEEE/OES Autonomous Underwater Vehicles

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Abstract-This paper reports the theory and implementation of a decentralized navigation system that enables simultaneous single-beacon navigation of multiple underwater vehicles. In single-beacon navigation, each vehicle uses ranges from a single, moving reference beacon in addition to its own inertial navigation sensors to perform absolute localization and navigation. In this implementation the vehicles perform simultaneous communication and navigation using underwater acoustic modems, encoding and decoding data within the acoustic broadcast. Vehicles calculate range from the time of flight of asynchronous acoustic broadcasts from the reference beacon. Synchronous clocks on the reference beacon and the vehicles enable the measurement of one-way travel-times, whereby the time of launch of the acoustic signal at the reference beacon is encoded in the acoustic broadcast and the time of arrival of the broadcast is measured by each vehicle. The decentralized navigation algorithm, running independently on each vehicle, is implemented using the information form of the extended Kalman filter and has been previously shown to yield results that are identical to a centralized Kalman filter at the instant of each range measurement. We summarize herein the architecture and design of the acoustic communications (Acomms) system consisting of an underwater acoustic modem, synchronous clock, and the software necessary to run them, and salient results from the validation of the decentralized information filter using a simulated data set.

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Section: Introductionmentioning

confidence: 99%

“…17 Prior efforts have proven observability of single beacon ranging through analysis of the Fisher Information Matrix 18 and which trajectories are observable. 17 Other work has examined optimal trajectories of a team of AUVs to enhance observability and thus improve the navigational accuracy. 19 Other works have investigated the use of multiple cooperating vehicles which share varying amounts of information to further constrain their navigation.…”

Section: Introductionmentioning

confidence: 99%

Closed‐loop one‐way‐travel‐time navigation using low‐grade odometry for autonomous underwater vehicles

Claus

Kepper

Suman

et al. 2017

Journal of Field Robotics

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This paper extends the progress of single beacon one-way-travel-time (OWTT) range measurements for constraining XY position for autonomous underwater vehicles (AUV). Traditional navigation algorithms have used OWTT measurements to constrain an inertial navigation system aided by a Doppler Velocity Log (DVL). These methodologies limit AUV applications to where DVL bottom-lock is available as well as the necessity for expensive strap-down sensors, such as the DVL. Thus, deep water, mid-water column research has mostly been left untouched, and vehicles that need expensive strap-down sensors restrict the possibility of using multiple AUVs to explore a certain area. This work presents a solution for accurate navigation and localization using a vehicle's odometry determined by its dynamic model velocity and constrained by OWTT range measurements from a topside source beacon as well as other AUVs operating in proximity. We present a comparison of two navigation algorithms: an Extended Kalman Filter (EKF) and a Particle Filter(PF). Both of these algorithms also incorporate a water velocity bias estimator that further enhances the navigation accuracy and localization. Closed-loop online field results on local waters as well as a real-time implementation of two days field trials operating in Monterey Bay, California during the Keck Institute for Space Studies oceanographic research project prove the accuracy of this methodology with a root mean square error on the order of tens of meters compared to GPS position over a distance traveled of multiple kilometers.

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A complete solution to underwater navigation in the presence of unknown currents based on range measurements from a single location

Cited by 95 publications

References 6 publications

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Advances in decentralized single-beacon acoustic navigation for underwater vehicles: Theory and simulation

Closed‐loop one‐way‐travel‐time navigation using low‐grade odometry for autonomous underwater vehicles

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