SeaPILOT - DVL Underwater Navigation

SeaPILOT

Doppler Velocity Logger (DVL) for underwater navigation on ROV, AUV and Vessels
The SeaPILOT Doppler Velocity Log (DVL) is ideal for unmanned submersible vehicle navigation applications and is available in 300 kHz, 600 kHz, and 1200 kHz models. The SeaPILOT OEM offers custom housing configurations for a diversifying submersible vehicle inventory.

Water Profile ranges from 0.08m to 150m
Bottom Track ranges from 0.3m to 300m


Key Features:

  • DVL - Doppler Velocity Logger
  • Light weight and small packages, or create your own housing with an OEM system
  • Depth rating from 300m to 6000m and can be packaged in Titanium, Aluminum or Plastic
  • Used for navigation and altitude on ROV, AUV, ASV and Ships
  • Integrated with Kearfott and GreenSea INS system. iXBlue INS coming soon.
  • Dual Frequency DVLs available
  • Upward/Downward looking ADCP with a single electronics package
  • Output industry standard formats: PD0, PD4, PD5, PD6, and PD13 data formats
  • Water Profile Range from 8cm to 150m
  • Bottom Track Altitude from 30cm to 300m
  • Pressure Sensor optionally available
  • Lithium batteries optionally available
  • External battery case optionally available
  • Realtime data processing or Record data to internal 32GB SD memory card and post process with software
  • Water Profile, Bottom Track and Water Track included
  • Bottom Track Long Range Mode included to gain 50% more range over industry standard Broadband mode
  • Output the industry standard formats plus our proprietary formats: RTB, RTD, PD0, PD3, PD4, PD5, PD6, PD13
  • RTB binary data format includes Beam, Instrument, Earth velocities, Echo Intensity, Correlation and NMEA
  • Connect a GPS directly to the ADCP and the NMEA data will be used and recorded with the ensemble data
  • Export to PD0, MATLAB, CSV and Python
  • Integrated with Hypack software suite.
  • Integrated with Aqua Vision software suite.
  • Up to 12 different configurations in a single deployment
  • Optional Ethernet communication available. Speeds up download time
  • Trigger In/Out available
  • Field replaceable transducers if any damage occurs to the ADCP
  • Modular electronic package
  • 8 Channel electronics to support up to 8 beams
  • OEM packaging available. You design your own head or housing. We supply the beams and electronics
  • Product comparisons with competitors


  • The SeaPILOT 300 kHz, 600 kHz, and 1200 kHz models are Rowe Technology’s most versatile DVLs. They use Rowe’s acoustic Doppler Piston (DP) technology and are well-suited for navigation applications in shallow water or in deep water, down to 6000M. The SeaPILOT’s compact size, extended range, and precision make it an ideal solution for ROVs, AUVs, and other submersible platforms.

    SeaPILOT comes in 3 different frequencies (300 kHz, 600 kHz, and 1200 kHz), all configured with Doppler Piston transducers, and available in different depth package options.

    The SeaPILOT OEM 300 kHz and 600 kHz models are available as an OEM configuration. They offer the same outstanding performance as the standard DVL package, but meet custom packaging requirements as found in small AUVs and submersibles.

    SeaPILOT OEM consists of an electronics board stack and four Doppler Piston transducers. Doppler Piston transducers are manufactured as separate elements and are not potted into the AUV housing. This facilitates easy installation and repair (6-inch AUV housing shown with machined “pockets” for the transducers).
    300kHz
    3" Beams
    600kHz
    3" Beams
    600kHz
    2" Beams
    600kHz
    1" Beams
    1200kHz
    2" Beams
    Water Profile:
    Broadband 100 m
    @ 4m Bin Size
    50 m
    @ 2m Bin Size
    45 m
    @ 2m Bin Size
    40 m
    @ 2m Bin Size
    20 m
    @ 1m Bin Size
    Narrowband 150 m
    @ 4m Bin Size
    75 m
    @ 2m Bin Size
    70 m
    @ 2m Bin Size
    50 m
    @ 2m Bin Size
    30 m
    @ 1m Bin Size
    Minimum Blanking Distance 32.0 cm 16.0 cm 16.0 cm 16.0 cm 8.0 cm
    Minimum Bin Size 2.8 cm 1.4 cm 1.4 cm 1.4 cm 0.7 cm
    Maximum Number of Bins 200 bins 200 bins 200 bins 200 bins 200 bins
    Velocity Resolution 0.01 cm/s 0.01 cm/s 0.01 cm/s 0.01 cm/s 0.01 cm/s
    Long-Term Accuracy ± 0.25%
    ± 2 mm/s
    ± 0.25%
    ± 2 mm/s
    ± 0.25%
    ± 2 mm/s
    ± 0.50%
    ± 1.5 mm/s
    ± 0.25%
    ± 2 mm/s
    BB Single Ping Precision 3.5 cm/s
    @ 4m bin size
    3.5 cm/s
    @ 2m bin size
    3.5 cm/s
    @ 2m bin size
    3.5 cm/s
    @ 2m bin size
    3.5 cm/s
    @ 1m bin size
    NB Single Ping Precision 20.0 cm/s
    @ 4m bin size
    20.0 cm/s
    @ 2m bin size
    20.0 cm/s
    @ 2m bin size
    20.0 cm/s
    @ 2m bin size
    20.0 cm/s
    @ 1m bin size
    Velocity Range ±5.0 m/s (Default); ±20.0 m/s (Maximum) ±5.0 m/s (Default); ±20.0 m/s (Maximum) ±5.0 m/s (Default); ±20.0 m/s (Maximum) ±10.0 m/s (Default); ±20.0 m/s (Maximum) ±5.0 m/s (Default); ±20.0 m/s (Maximum)
    Amplitude Dynamic Range 100 dB 100 dB 100 dB 100 dB 100 dB
    Amplitude Presicion 0.001 dB 0.001 dB 0.001 dB 0.001 dB 0.001 dB
    Bottom Track:
    Minimum Altitude 0.5 m 0.3 m 0.3 m 0.3 m 0.3 m
    Maximum Altitude 300 m 130 m 120 m 70 m 50m
    Long-Term Accuracy ± 0.70%
    ± 2 mm/s
    ± 0.25%
    ± 2 mm/s
    ± 0.50%
    ± 2 mm/s
    ± 0.50%
    ± 1.5 mm/s
    ± 0.25%
    ± 2 mm/s
    Single Ping Precision 0.6 cm/s
    @ 3 m/s
    0.5 cm/s
    @ 3 m/s
    0.5 cm/s
    @ 3 m/s
    1.5 cm/s
    @ 1.0 m/s
    0.4 cm/s
    @ 3 m/s
    Data:
    Communcations [RS-232 & RS-485], [RS-422], [Ethernet (UDP)]
    Ping Rate Up to 10 hz Up to 10 hz Up to 10 hz Up to 10 hz Up to 10 hz
    Internal Recording 32 GB Micro SD Card
    Data Formats RTB, RTD, PD0, PD3, PD4, PD5, PD6, PD13, MATLAB, CSV, Python
    Sensors:
    Compass Range: 0°-360°, Accuracy: 1° RMS, Resolution: 0.01°
    Pitch/Roll Range: Roll ±180° | Pitch ±90°, Accuracy: < 1° RMS, Resolution: 0.01°
    Water Temp Range: -5° - 70°C, Accuracy: ±0.15°C
    Pressure Range: Selectable, Accuracy: ±0.1% Range
    System:
    Transducer Size 3 in 3 in 2 in 1 in 2 in
    Configurations 4-Beam, 5-Beam, 7-Beam, 8-Beam
    Beam Width 2.80° 1.42° 2.16° 3.50° 1.01°
    Beam Angle 20° 20° 20° 20° 20°
    Voltage Range 12 - 36 Volt DC
    Average Power 23 W 30 W 30 W 30 W 23 W
    Temperature -5° to 45° C (Operating), -30° to 60° C (Storage)
    Depth Rating 300m, 3000m, 4000m, 6000m
    Material Options Acetal(Plastic), Aluminum, Titanium
    Specifications may be subject to change at any time in the future

    FlatFish AUV with Dual Frequency 300khz/1200khz

    Placement of FlatFish's components (sensors, thrusters etc.)

    FlatFish is an autonomous underwater vehicle (AUV) for repeated inspections of oil & gas subsea structures whilst being submerged for extended periods of time.

    LENG AUV with Dual Frequency 1200khz/1200khz Up/Down

    The autonomous underwater vehicle (AUV) Leng was designed as long-distance exploration vehicle. Its shape was specifically designed to meet the requirements of the Europa-Explorer-Project: very small diameter (in order to fit into the ice drill) as well as a hydrodynamically optimized outer hull (in order to reduce energy consumption and enable long-range missions). The vehicle is equipped with a large number of different navigation sensors since localization quality and availability are of key importance – in the Europa-Explorer-scenario the vehicle has to return to its starting position (ice drill) even after having conducted long-distance missions.

  • ROV, AUV, USV and Ship Navigation
  • Oceanographic Coastal Shores Measurements
  • Sediment Discharge Measurements
  • Boundary Layer Measurements
  • Tidal Measurements
  • Reynolds Stress
  • Offshore Oil and Gas Exploration and Drilling
  • Renewable Energy
  • Oceanographic Research
  • Aquaculture and Fisheries
  • Navigation Safety in Ports and Harbors
  • Coastal and Ocean Engineering Site Assessment
  • Environmental Management
  • Deep and Midwater Moorings, Buoys and Sea-Floor Applications
  • Port and Harbor Dredging
  • Coastal Ocean and Port Surveying
  • Meteorological and Wave Data Acquisition
  • River Discharge Measurements
  • Arctic Ice Tracking
  • Academic Research
  • Gallery

    Note: Click on the heading text to expand or collapse panels to read the abtracts.

    Currently the inspection of industrial underwater structures is performed by remotely operated vehicles or by divers. Since the number of underwater structures keeps growing, e.g. due to new oil and gas fields or offshore wind farms, the need for a constantly available method to inspect these structures arises. The FlatFish project is an initiative of BG Group Brazil and the Brazilian Institute of Robotics in Salvador and aims at developing a subsea-resident AUV which can inspect the infrastructure at an oil and gas site on demand. FlatFish is a compact AUV, designed to acquire a high-resolution, textured 3D model of an underwater structure within an oil and gas asset. FlatFish is very agile and can hover during inspection, it uses a novel kind of navigation system to safely reach its goal within the field and is designed to stay submerged for extended periods of time. Within this paper the system design of FlatFish is presented.

    DOI: 10.23919/OCEANS.2015.7404442
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    Placement of FlatFish's components (sensors, thrusters etc.)
    This paper presents a manifold based Unscented Kalman Filter that applies a novel strategy for inertial, model-aiding and Acoustic Doppler Current Profiler (ADCP) measurement incorporation. The filter is capable of observing and utilizing the Earth rotation for heading estimation with a tactical grade IMU, and utilizes information from the vehicle model during DVL drop outs. The drag and thrust model-aiding accounts for the correlated nature of vehicle model parameter error by applying them as states in the filter. ADCP-aiding provides further information for the model-aiding in the case of DVL bottom-lock loss. Additionally this work was implemented using the MTK and ROCK framework in C++, and is capable of running in real-time on computing available on the FlatFish AUV. The IMU biases are estimated in a fully coupled approach in the navigation filter. Heading convergence is shown on a real-world data set. Further experiments show that the filter is capable of consistent positioning, and data denial validates the method for DVL dropouts due to very low or high altitude scenarios.

    arXiv:1805.08011v1 [cs.RO] 21 May 2018
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    The FlatFish AUV [2] during sea trails. Image: Jan Albiez, SENAI CIMATEC
    Water current velocities are a crucial component of understanding oceanographic processes and underwater robots, such as autonomous underwater vehicles (AUVs), provide a mobile platform for obtaining these observations. Additionally, a real-time estimate of the water-current velocity environment will aid the control and planning of the AUV, and localizing within a predicted water-current vector field is an area of continuing research [1]. Estimating water current velocities requires both measurements of the water velocity, often obtained with an Acoustic Doppler Current Profiler (ADCP), as well as estimates of the vehicle velocity.

    ICRA 2016 Workshop on Marine Robot Localization and Navigation
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    The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown.

    Sensors (Basel). 2017 Feb; 17(2): 415.
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    Platform frame and tangent frame in respect to the TAUV.

    ADCP/DVL and ROV with beams shown from TAUV.
    This work proposes a localization method using a mechanically scanned imaging sonar (MSIS), which stands out by its low cost and weight. The proposed method implements a Particle Filter, a Bayesian Estimator, and introduces a measurement model based on sonar simulation theory. To the best of author’s knowledge, there is no similar approach in the literature, as sonar simulation current methods target in syntethic data generation, mostly for object recognition . This stands as the major contribution of the thesis as allows the introduction of the computation of intensity values provided by imaging sonars, while maitaining compability with the already used methods, such as range extraction. Simulations shows the efficiency of the method as well its viability to the utilization of imaging sonar in underwater localization. The new approach make possible, under certain constraints, the extraction of 3D information from a sensor considered, in the literature, as 2D and also in situations where there is no reference at the same horizontal plane of the sensor transducer scanning axis. The localization in complex 3D environment is also an advantage provided by the proposed method.



    Rio de Janeiro: UFRJ/COPPE, 2017.
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    Cochin Port is a major port in the Arabian Sea – Indian Ocean Sea – route and is one of the largest ports in India. The commercial port of Cochin in South-East India is situated in a natural bay connected to Kerala’s backwaters. It has the largest siltation rate among Indian ports: more than 20 million m³ per year. Siltation is pollution of water by fine particulate terrestrial clastic material. Siltation occurs mostly during the Monsoon (June-September) when both river discharges and ocean dynamics are high.

    The need for continuous maintenance dredging has serious budgetary impacts for the Cochin Port Trust (COPT). Therefore Cochin Port Trust assigned Antea Group, IIC technologies and Stema Systems to collaborate on a study for the analysis of the siltation processes and to assess the feasibility to implement the nautical depth concept. The latter signifies to investigate the nature of the fluid mud seabed and determine to what extent vessels can sail through and manoeuvre in it.

    Wodcon XXI Proceedings 2016.
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    The port of Cochin has the largest siltation rate among Indian ports: +20 million m³/year. Local dynamics are controlled by the two rivers discharging into the port system and the ocean. Siltation occurs mostly during the Monsoon (June-September) when dynamics are high (Naik et al., 1983). The Cochin Port Trust (COPT) has tried to optimize the dredging efforts, i.e. allowing ships to partially penetrate the fluid mud. This project is a comprehensive attempt to tackle this problem by understanding the siltation processes in detail and by determining a minimum water depth, draft and under-keel-clearance at which navigation of ships through fluid mud is “safe” (nautical depth). The project was structured in different stages: 1. Desktop study to understand the existing situation and to determine the required acquisition efforts for the development of a numerical 2D model (TELEMAC6 ). 2. Data acquisition and fieldwork to gather the key variables to set up and calibrate the numerical model and undertake the navigation studies. 3. Numerical modeling to understand in detail the siltation processes that occur in the area by simulating the hydrodynamics conditions (waves, tides and currents) as well as sediment transport, erosion and siltation processes. After calibration and validation, the model was used for scenario analysis. 4. Navigation studies to determine a nautical depth. Firstly, the navigation conditions were modeled physically by replicating (1) natural conditions under laboratory environment, (2) selecting a number of maneuvers with chosen design ships with different under keel clearance (UKC) levels and (3) determining mud rheology at the towing tank from the Flanders Hydraulics Research (FHR). Secondly, the results obtained in the physical model were compared against the expert judgement of pilots from the Port of Cochin. For this, tests in the 3D navigation simulator from the FHR, replicating Cochin’s hydrodynamic and environmental conditions, were developed. For this project, the nautical depth criterion was defined with a conservative mindset, by assessing “safe navigation” in terms of maneuverability of vessels. Recommendations to support the implementation of this criterion were provided to the client. The combination of all achieved results allowed the COPT to optimize their maintenance dredging strategy, while keeping sufficient nautical depth. In order to reach greater economic success, the nautical depth criterion needs to be fine-tuned in future works.

    CEDA Dredging Days 2017, At Rotterdam
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    The North Carolina State University’s Department of Marine, Earth, and Atmospheric Sciences and Center for Marine Science and Technology recently acquired a SeaRobotics MiniCat Unmanned Surface Vehicle (USV). The USV is designed to operate in shallow water, coastal, harbor, riverine, and lake environments. The USV can operate with two different instrument configurations. 1) A seabed-mapping package with an Edgetech 6205 bathymetric and side-scanning sonar with integrated sub-bottom profiler, or 2) a watercolumn mapping package with a Rowe 1200Khz Seaprofiler Acoustic Doppler Current Profiler (ADCP) and multi-component data logger which collects information on water temperature and salinity, as well as the concentration of Chlorophyll-a and dissolved organic matter. The USV has been deployed to Lake Raleigh, Falls Lake, and the North Carolina coast. Initial sea trials and validation have focused on the use of the seafloor-mapping package. Both the side-scan and the bathymetric data collected by the USV have the capability to resolve sub-meter features on the seabed or lake floor. Such high-resolution data will allow the USV to be used for detailed habitat mapping, monitoring of coastal restoration efforts and geo-hazard studies. The water-column mapping package will be used for environmental and water quality studies along coasts and lakes throughout the southeastern United States.

    NC State University Undergradute Research Symposium 2016.
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    SeaRobotics USV using a Rowe Technologies SeaProfiler ADCP/DVL.
    SeaRobotics USV using a Rowe Technologies SeaProfiler ADCP/DVL.
    SeaRobotics USV using a Rowe Technologies SeaProfiler ADCP/DVL.
    Changes of subaqueous topography in shallow offshore water pose safety risks for embankments, navigation, and ports. This study conducted measurements of subaqueous topography between Datong and Xuliujing in the Yangtze River using a SeaBat 7125 multi-beam echo sounder, and the channel change from 1998 to 2013 was calculated using historical bathymetry data. The study revealed several important results: (1) the overall pattern of changes through the studied stretch of the river was erosion–deposition–erosion. Erosion with a volume 700×10⁶ m³ occurred in the upper reach, deposition of about 204×10⁶ m³ occurred in the middle reach, and erosion of about 602×10⁶ m³ occurred in the lower reach. (2) Dunes are the most common microtopographic feature, accounting for 64.3% of the Datong to Xuliujing reach, followed by erosional topography and flat river topography, accounting for 27.6% and 6.6%, respectively. (3) Human activities have a direct impact on the development of the microtopography. For instance, the mining of sand formed holes on the surface of dunes with lengths of 20–35 m and depths of 3–5 m. We concluded that the overall trend of erosion (net erosion volume of 468×10⁶ m³) occurred in the study area mainly because of the decreased sediment discharge following the closure of the Three Gorges Dam. However, other human activities were also impact factors of topographic change. Use of embankments and channel management reduced channel width, restricted river meandering, and exacerbated the erosion phenomenon.

    Science China Earth Science 61(7) · April 2018
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    In this software project, the design and implementation of a modular Acoustic Doppler Current Profiler (ADCP) parser is presented. The application was developed as a software project for General Acoustics e.K. a company residing in Kiel, Germany. The reasons that lead to this software project originated in a project in the Iraq. The decision to move the ADCP data parsing location from the onshore server to an offshore platform required the implementation of a platform independent parser. The goal was to create a flexible, efficient, component based, and portable solution to parse ADCP data. The design of the application should also allow later extension with new functionality. It was implemented in modern C++11 using the Boost C++ libraries and a thread-based architecture.

    SOFTWARE PROJECT – Communication Systems Group, Prof. Dr. Burkhard Stiller 2016
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    The 2016 demonstration cruise of the MIDAS project was conducted to apply existing and novel methods for habitat mapping in a real-world scenario to investigate their applicability to deep sea mining scenarios. With the help of the excellent NIOZ RV Pelagia and their fantastic crew, different image sampling strategies were conducted to better understand their feasibility and practicality. All stations were conducted at Condor seamount off the coast of the island of Faial (Azores, Portugal).


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    Rowe Technologies SeaPILOT DVL attached to NIOZ HD Hopper.
    A pair of self-contained acoustic Doppler current profilers (SC-ADCPs) operating with different frequencies were moored on a muddy sea bottom at about 20 m depth in the Bay of Vilaine off the French Atlantic coast. With their acoustic beams oriented upwards, the SC-ADCPs ensonified most of the water column. The results of several months of in situ recorded echo intensity data spanning 2 years (2003 to 2004) from the dual-frequency ADCPs are presented in this paper. The aim was to estimate suspended particle mass concentration and mean size. A concentration index CI is proposed for the estimation of particle concentration. Based on theory the CI—unlike the volume backscatter strength—does not depend on particle size. Compared with in situ optical data, the CI shows reasonable precision but not increased with respect to that of the highest-frequency backscatter strength. Concerning the mean particle size, despite a lack of quantitative validation with optical particle-size measurements, the method yielded a qualitative discrimination of mineral (small) and organic (large) particles. This supports the potential of dual-frequency ADCPs to quantitatively determine particle size. A cross-calibration of the transducers of each ADCP shows that a specific component of the precision of the backscatter strength measured by ADCP depends on the acoustic frequency, the cell thickness and the ensemble integration time. Based on these results, the use of two ADCPs operating with distinctly different frequencies (two octaves apart) or a single dual-frequency ADCP is recommended.


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    This summer research project aimed to achieve several distinct goals. The principal goal was to transform the body of an Unmanned Surface Vessel (USV), specifically a Wave Adaptive Modular Vessel (WAMV), into an autonomous mothership for a Remotely Operated Vehicle (ROV), the VideoRay Pro 4. Another challenge addressed by the research team was finding a way to permanently mount an acoustic Doppler Velocity Log (DVL) to the VideoRay without significantly hindering the VideoRay’s performance. Lastly, the team was tasked with understanding how the DVL recorded data, and how that data could be used to determine location. The Maritime Security Center Summer Research Institute ROV team, located at Stevens Institute of Technology, conducted eight weeks of research to find solutions to these unique challenges.


    VideoRay with a SeaPILOT attached.
    Maritime Security Center, A Department of Homeland Security Science and Technology Center of Excellence, 2017.
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