Experiments in Moving Baseline Navigation using Autonomous Surface Craft

Curcio, J. A.; Leonard, John J.; Vaganay, J.; Patrikalakis, A.; Bähr, Alexander; Battle, David; Schmidt, Henrik; Grund, M.

doi:10.1109/oceans.2005.1639839

Cited by 93 publications

(52 citation statements)

References 8 publications

(9 reference statements)

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“…Equations (1) through (6) in the previous sections were used to mathematically simulate two tracking stations at a fixed radius of 2.83 m from the tracked object. The sensors for each tracking station were identical, as in Case 1, and were given an angular error of 0.1 radians and a radial error of 0.4 m to match the quadrotor sensor parameters.…”

Section: Mathematical Simulation Of Two Tracking Stations At a Fixed mentioning

confidence: 99%

“…This can be avoided by moving the sensors to follow the tracked object. In [6], tracking experiments were performed using acoustic modems to measure ranges between vehicles. A leader-follower setup was used in which the lead vehicle was an underwater vehicle which acted as the target and the following vehicles were surface craft which acted as sensor systems.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Sensor Locations in a Multisensor Single-Object Tracking System

Cashbaugh

Kitts

2015

International Journal of Distributed Sensor Networks

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Tracking a mobile object presents many challenges, especially when the tracked object is autonomous or semiautonomous and may move unpredictably. The use of autonomous mobile sensor systems allows for greater opportunity to track the mobile object but does not always yield an estimate of the tracked object's location that minimizes the estimation error. This paper presents a methodology to optimize the sensor system locations, given a single object and a fixed number of sensor systems, to achieve a position estimate that minimizes the estimation error. The tracking stations may then be controlled to achieve and maintain this optimal position, under position constraints. The theory predicts that given n sensor systems and one object there is a sensor system configuration that will yield a position estimate that minimizes the estimation error. A mathematical basis for this theory is presented and simulation and experimental results for two and three sensor system cases are shown to illustrate the effectiveness of the theory in the laboratory.

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Section: Mathematical Simulation Of Two Tracking Stations At a Fixed mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing Sensor Locations in a Multisensor Single-Object Tracking System

Cashbaugh

Kitts

2015

International Journal of Distributed Sensor Networks

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“…Acoustic modem drivers previously reported by the authors and others for synchronous navigation, such as the modem drivers employed on the MIT autonomous surface vehicles, [3], and the WHOI Seabed vehicles, [4], [6], are not portable due to the tight integration of these modem drivers into the vehicle-specific application code of their respective vehicle control and navigation systems. In contrast, the Acomms software reported herein is portable, employs a vehicle-independent interface based on UDP messages, runs as a stand-alone daemon on a host Linux CPU, and operates symmetrically on all node types -e.g.…”

Section: Acomms Softwarementioning

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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“…PID control based on GPS and compass data is supported by the free software, Linux-based, MOOS operating program [13]. Main applications focused on the implementation of basic systems of autonomous navigation in accordance with the rules of the road (Coast Guard Collision Regulations -COLREGS) [14] and the use of ASC for developing and testing of distributed acoustic navigation algorithms for undersea vehicles [15].…”

Section: A Asc For Education and Civil Applications In Usamentioning

confidence: 99%