ROAM@CRAS - A haRbor multidOmAin Mapping dataset

The ROAM@CRAS dataset was acquired using an Autonomous Surface Vehicle (ASV), the SENSE, equipped with a set of incorporated sensors for perceiving the surface and underwater domains (Velodyne VLP-16, Mynt Eye D and Imagenex ”Delta T” 837B) as well as navigation sensors such as L1/L2 RTK, GPS and IMU. This dataset was acquired during a campaign of the project DIIUS (Distributed perceptIon for inspectIon of aqUatic Structures) on the harbor of Marina de Leça, Porto, Portugal ( The ASV was remotely operated at all time performing a trajectory with distinct challenges for 3D mapping and sensor fusion applications, such as data imperfecteness, inconsistency and heterogeneity. All data was recorded using ROS bags each with ~14s duration to be played in sequence all together taking up to the total mission time (~1196s). The dataset provides a perspective of both domains available on the maritime environment, namely the surface and the underwater domains, giving essencial research data for maritime robotic platforms to increase the situational awareness and enhance the 3D mapping capacities to provide a more complete representation of the surroundings. For downloading the SENSE tfs, launches and more details check the github repository -

Each bag is composed by the following topics:

/cmd_vel: geometry_msgs/Twist - Velocity command from the control station

/gps/basestation_ecef: nav_msgs/Odometry - Swift Navigation Piksi Multi RTK base station position in ECEF

/gps/fix: sensor_msgs/NavSatFix - Swift Navigation Piksi Multi GPS position

/gps/rtkfix: nav_msgs/Odometry - SENSE Swift Navigation Piksi Multi GPS RTK odometry

/gps/time: sensor_msgs/TimeReference -Swift Navigation Piksi Multi GPS Time reference

/imu/data: sensor_msgs/Imu - Xsens MTi-30 IMU data

/imu_nav/data: sensor_msgs/Imu - Sparkfun Razor IMU 9DOF data

/left/cmd: roboteq_msgs/Command - Left thruster command for Roboteq

/mbes/scan: sensor_msgs/LaserScan - Imagenex ”Delta T” 837B scan

/mynteye/depth/camera_info: sensor_msgs/CameraInfo - Mynt Eye D camera parameters

/mynteye/depth/image_raw: sensor_msgs/Image - Mynt Eye D depth image

/mynteye/left/image_color/compressed: sensor_msgs/CompressedImage - Mynt Eye D left image

/mynteye/right/image_color/compressed: sensor_msgs/CompressedImage - Mynt Eye D right image

/right/cmd: roboteq_msgs/Command - Right thruster command for Roboteq

/roboteq_driver/status: roboteq_msgs/Status - Roboteq status feedback

/safety_stop: std_msgs/Bool - Emergency failsafe status

/ublox_nav/fix: sensor_msgs/NavSatFix - Vk-162 Glonass Navigation USB GPS position data

/ublox_nav/fix_velocity: geometry_msgs/TwistWithCovarianceStamped - Vk-162 Glonass Navigation USB GPS velocity data

/velocity: geometry_msgs/TwistStamped - Angular velocity published by the Xsens MTi-30 IMU

/velodyne_points: sensor_msgs/PointCloud2 - Velodyne VLP-16 Point cloud

Data and Resources

Additional Info

Field Value
Source Project DIIUS - Distributed perceptIon for inspectIon of aqUatic Structures -
Author Daniel Filipe Campos
Last Updated February 18, 2021, 10:34 (Europe/Lisbon)
Created September 11, 2020, 18:49 (Europe/Lisbon)
CiteAs CAMPOS, D.F., LEITE, P.N., SILVA, R., PEREIRA, M.I., MARQUES, R., PINTO, A.M. ROAM@CRAS - A haRbor multidOmAin Mapping dataset [dataset]. 11 September 2020. INESC TEC research data repository. DOI:
dc.Contributor Pedro Nuno Leite; Renato Silva; Maria Inês Pereira; Rafael Marques; Andry Maykol Pinto
dc.Coverage.Spatial Marina de Leça, Porto, Portugal
dc.Coverage.Temporal 20 min during the morning of 09 July 2020
dc.Date 09 July 2020
dc.Format *.bag
dc.Format.Extent XXGB
dc.Language EN
dc.Publisher INESC TEC
dc.Type ROS Bag (.bag)
ddi.NameInstrument SENSE with GPS (Swift Navigation Piksi Multi and Vk-162 Glonass Navigation), IMU (Xsens MTi-30 and Sparkfun Razor IMU 9DOF), 3D LiDAR (Velodyne VLP-16), Multibeam Echosounder (Imagenex ”Delta T” 837B), Stereo Camera (Mynt Eye D)
ddi.Software Software: ROS Melodic
ddi.TypeInstrument Autonomous Surface Vehicle with GPS, IMU, 3D LiDAR, Multibeam Echosounder, Stereo Cameras