SL Sensor is an open-source, ROS-based, structured light sensor for high-accuracy 3D scanning. It can produce high-fidelity point clouds in real-time at 5Hz using hardware triggering of the camera and the projector.

Refer to the Wiki pages for the wiring schematics, CAD as well as steps to calibrate/setup the sensor.

The sample build we have provided contains two cameras (because we want it as a research platform to test our linear motion compensation strategy in both directions) but it can be modified to work with only one camera as well.

Some experience with C++ and ROS is required to troubleshoot and configure roslaunch files to make it work on your system.

• Computer/Laptop with at least one USB3 Port
• Ubuntu 18.04 with ROS Melodic installed
• Required Libraries (* included in 18.04 installation)
  • *yaml-cpp (Version 0.5.2)
  • *OpenCV 3.2.0
  • *Point Cloud Library PCL (Version 1.8)
  • Spinnaker (Version 2.4.0.143)
  • Open3d (Version 0.13.0) NOTE: Please refer to this issue to ensure that you can build and install Open3d so that it is ROS-compatible

• sl_sensor_calibration: Calibration utilities for the SL Sensor
• sl_sensor_codec: Generate different structured light patterns (encoding) and processing images to obtain projector coordinates (decoding)
• sl_sensor_image_acquisition: Group images that are from the same pattern sequence together from timestamped image streams from Versavis
• sl_sensor_logger: Logging utilities to save images and point clouds
• sl_sensor_motion_compensation: Motion compensation algorithm that enables scanning while in motion (constrained to linear motion at the moment)
• sl_sensor_reconstruction: Converts decoded projector coordinate images into point clouds
• sl_sensor_registration: Basic utilities to register point cloud in a pairwise fashion using ICP
• sl_sensor_rqt_gui: Simple GUI for calibration and scanning
• sl_sensor_timer: Basic timing utilities

1. Set up your Personal Access Token so you can clone over SSH
2. Install ros-melodic
3. Clone this repository into the src folder of your workspace
4. Configure your workspace to build in release: catkin config --cmake-args -DCMAKE_BUILD_TYPE=Release
5. Install vcstool and catkin-tools from apt: sudo apt install python3-catkin-tools python3-vcstool
6. From the src folder of your workspace, clone source dependencies with vcs tool: vcs import < sl_sensor/dependencies.vcs
7. From the src folder of your workspace, install the system dependencies with rosdep: rosdep install --from-paths . --ignore-src -r -y
8. Build the FLIR camera driver catkin build flir_camera_driver
9. Build the SL Sensor package catkin build sl_sensor
10. To ensure the scannning RQt dashboard loads properly, change the directories in the following RQt perspective files to reflect the actual location in your computer
    • sl_sensor/core/sl_sensor_rqt_guis/sl_sensor_rqt_guis_common/rqt_perspectives/scan_gui_monochrome.perspective:
      Change line 527 ("repr": "u'/home/ltf/catkin_ws/src/sl_sensor/sl_sensor/rviz/scan_rqt_gui_monochrome.rviz'")
    • sl_sensor/core/sl_sensor_rqt_guis/sl_sensor_rqt_guis_common/rqt_perspectives/scan_gui_colour.perspective:
      Change line 527 ("repr": "u'/home/ltf/catkin_ws/src/sl_sensor/sl_sensor/rviz/scan_rqt_gui_colour.rviz'")

1. Download the parameter files and rosbags from here
2. Replace core/sl_sensor_codec/codec_yaml/codec_config.yaml with the codec_config.yaml in the downloaded folder parameter_files
3. Replace the xml files primary_camera.xml, secondary_camera.xml, projector.xml core/sl_sensor_calirbation/calibration_files with those in the downloaded folder parameter_files
4. Start a roscore in a terminal by running roscore
5. On a separate terminal run rosparam set /use_sim_time true
6. Roslaunch the reconstruction pipeline that has the same pattern name as the rosbag in the downloaded folder
   • For example, if you want to run rosbag play --clock 2p1_tpu_horizontal.bag (make sure terminal is in the 2p1_tpu_horizontal folder)
   • Run roslaunch sl_sensor 2p1_tpu_horizontal_motion_compensation.launch to see motion compensation in action
   • Run roslaunch sl_sensor 2p1_tpu_horizontal.launch if you want to see the distortion due to motion if a standard reconstruction pipeline is used

This repo contains code adapted from:

• Reconstruction pipeline components - SLStudio
• Bundle Adjustment dual camera-projector calibration (experimental) IDIAP Multicam Calibration