//==================================================================== module = iBlueROV_CommandAndControl type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = Sending MOOS commands to BlueROV2 via Mavlink. synopsis = iBlueROV_CommandAndControl is a MOOS app that can be run on the Raspberry Pi Companion Computer onboard the BlueROV2. The app is able to send MOOS based commands to BlueROV2 via Mavlink. MOOS commands include arming/disarming, mode changing (i.e. MANUAL, AUTO, GUIDED, DEPTHHOLD, STABILIZED modes) and, desired depth, heading and speed commands. The autonomous modes of BlueROV2 (i.e. AUTO and GUIDED modes) are not stable at the time of writing; therefore, desired commands are sent in DEPTHHOLD mode as thrust inputs, computed by a low level control system within iBlueROV_CommandAndControl. This app was initially developed to send commands to BlueROV by MIT’s Autonomous Surface Vehicle (ASV), REx4. The BlueROV was connected to REx4 using an automated winch and MOOS commands were sent from REx4’s MOOSDB to the ROV’s MOOSDB using pShare. distro = https://github.mit.edu/AUVLab group = BlueROV, Mavlink, Drivers, ASV-ROV borndate = 190110 doc_url = https://github.mit.edu/AUVLab //==================================================================== module = iBlueROV_DataReceiver type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = Receiving navigation data from BlueROV2 via Mavlink. synopsis = iBlueROV_DataReceiver is a MOOS app that can be run on the Raspberry Pi Companion Computer onboard the BlueROV2. The app receives navigation information from BlueROV2 (such as current depth, heading and throttle) and publishes them in MOOSDB. This app was initially developed to receive navigation information from a BlueROV2 to MIT’s Autonomous Surface Vehicle (ASV), REx4. The BlueROV was connected the REx4 using an automated winch and navigation information published in ROV’s MOOSDB were shared with REx4’s MOOSDB using pShare. distro = https://github.mit.edu/AUVLab group = BlueROV, Mavlink, Drivers, ASV-ROV borndate = 190110 doc_url = https://github.mit.edu/AUVLab //==================================================================== module = pHydroMAN_BasicModel type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A hydrodynamic model aided navigation system for AUVs. synopsis = pHydroMAN_BasicModel is one of the core apps of Hydroman Toolbox. It uses the last GPS update, propeller RPM, vehicle roll, pitch, heading angles and control surface angles received from AUV's frontseat, and computes linear velocities of the AUV in both body-fixed and earth-fixed reference frames (i.e. u, v, w and xdot, ydot and zdot). The dynamic model based localization solution is also computed for low-cost AUVs with no DVL, LBL/USBL or INS. The hydrodynamic parameters of the AUV are to be configured in the configuration file. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Sensors borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = pHydroMAN_DVLProcessor type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A MOOS app that configures a DVL for under-ice AUV navigation. synopsis = pHydroMAN_DVLProcessor is an under-ice navigation related app within Hydroman Toolbox. It uses surface ice drifting speed & heading received from top-side (i.e. ice camp) to compensate the ice-tracking DVL measurements for ice motion. The app also gives the capability to dynamically re-configure the axis frame of the DVL from top-side via a hydroman_engineering DCCL message (this can be useful if the DVL was changed from downward facing to upward facing). distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Sensors, DVL, Under-ice borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = pHydroMAN_LBLProcessor type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A MOOS app that corrects the time-lag of an acoustic position fix. synopsis = pHydroMAN_LBLProcessor is one of the acoustic positioning related apps of Hydroman Toolbox. The apps is able to extrapolate time-lagged acoustic position updates (e.g. LBL or USBL) and correct their co-variance matrix to the current time-stamp using the vehicle dynamic model. This is useful for long range and two-way transmission acoustic positioning systems with time delays/lags. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Sensors, LBL, Acoustic-tracking borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = pHydroMAN_ModelCalibrator type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A MOOS app that calibrates the basic AUV dynamic model in real-time. synopsis = pHydroMAN_ModelCalibrator MOOS app calibrates the basic model based localization solution (i.e. the output from pHydroMAN_BasicModel) to the current operating environment and counteracts the drift in model based position when reliable acoustic position fixes are available. The app posts the calibrated model based AUV velocity and position solution. It is able to process time-lagged acoustic position updates if required. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Sensors borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = pHydroMAN_SensorFusion type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = An EKF based sensor fusion app for AUV navigation synopsis = pHydroMAN_SensorFusion is one of the core apps of Hydroman Toolbox, which fuses navigation sensor measurements (i.e. including DVL bottom/ice – track measurements, acoustic position updates and INS data) with a vehicle dynamic model to compute a low-drift localization and navigation solution. Sensor fusion and state estimation is achieved with an EKF, and a secondary EKF is in place to estimate the sensor error states (i.e. to estimate bias errors of DVL, INS and dynamic model). The essential purpose of this app is similar to that of the pNav code written by Prof. Paul Newman. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Sensors, Fusion, EKF borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = uSimDVL type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A DVL simulator for navigation simulations synopsis = uSimDVL is a simulation utility of Hydroman Toolbox, that computes and posts DVL velocity measurements of a simulated AUV. The app is configurable for DVL bottom-tracking, ice-tracking and water-tracking modes. The DVL update frequency, standard deviation and bias error can be set from the configuration file. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Simulation, DVL borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = uSimLBL type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A simulator of an LBL system for navigation simulations synopsis = uSimLBL is a simulation utility of Hydroman Toolbox, that publishes simulated acoustic position fixes and error co-variance information for a simulated AUV. A position update frequency and/or update time-lag can be set in the configuration file. The standard deviation and bias error of the LBL position fixes are also configurable. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Simulation, LBL, USBL borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = uSimPhinsINS type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = An IxBlue INS simulator for navigation simulations synopsis = uSimPhinsINS is a simulation utility of Hydroman Toolbox, which simulates IxBlue PHINS 3 INS unit. The app publishes acceleration, velocity, attitude and measurement uncertainty data for the simulated AUV using the same output format as iHydroMAN_PHINS app. The standard deviation, bias error and scale error of acceleration measurement are configurable. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Simulation, INS, IxBlue borndate = 190110 doc_url = https://github.mit.edu/lamss //==================================================================== module = uSimReplayPCAP type = MOOS App author = Supun Randeni contact = supun@mit.edu org = MIT thumb = A MOOS app that can replay a PCAP file over UDP. synopsis = uSimReplayPCAP is a simulation utility of Hydroman Toolbox that can replay a *.PCAP file (packet capture file) over UDP. The location of the PCAP file, IP address and port are configurable. This utility tool can be useful for development and testing of drivers that phrase data received over UDP. distro = https://github.mit.edu/lamss group = Navigation, Localization, Hydroman, Simulation, DVL borndate = 190110 doc_url = https://github.mit.edu/lamss