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PTG ANGEL System

Initial repo for PTG project.

This repo contains:

  • Experimental Unity app (and companion HL2SS plugin) for transmitting appropriate sensor data off of the HoloLens2 platform, and for running the ANGEL ARUI.
  • ROS 2 system for receiving sensor data, processing analytics, and pushing results out.

Note: This repository contains submodules that will need to be initialized upon first checkout:

$ git submodule update --init --recursive

Windows Development for HL2

Tool versions used

Unity Hub - 3.0.0 - https://unity.com/unity-hub
Unity - 2020.3.25f1 - https://unity3d.com/get-unity/download/archive
Visual Studio 2019 - 16.11.8 - https://visualstudio.microsoft.com/vs/older-downloads/
Mixed Reality Feature Tool - 1.02111-Preview - https://www.microsoft.com/en-us/download/details.aspx?id=102778
HoloLens 2 headset - OS version 20438.1432
Anaconda/Miniconda - py3.9
HL2SS plugin - 1.0.15 - https://github.com/jdibenes/hl2ss

First time build/deploy instructions

  1. Open the unity/ARUI project with Unity Hub.
  2. Open the arui_engineering scene in the Unity editor (unity\ARUI\Assets\my_scene).
  3. Modify the default project build settings (File -> Build Settings...).
    • Ensure the "Scenes/arui_engineering" scene is checked for inclusion in the build (others may be unchecked).
    • Under the Universal Windows Platform tab
      • Target Device = HoloLens
      • Architecture = ARM64
      • Minimum Platform Version = 10.0.19041.0
      • Build and Run on = USB Device
    • Click Switch Platform after applying the new settings.
  4. Follow the instructions in the ROS Unity setup section to generate the message files and set the endpoint IP.
  5. Create a build folder to place completed Unity builds (e.g. unity/ARUI/Build).
  6. Click Build and specify your desired build folder. After the build completes, a new file explorer windows will pop up with the location of the build.
  7. Open the .sln file with Visual Studio.
  8. In Visual Studio, switch Solution Configurations to Release and Solution Platforms to ARM64.
  9. Open the project properties window (In the Solution Explorer pane, right-click Angel_ARUI and select Properties) and switch to the Configurations -> Debugging tab. Enter the IP address of your HoloLens in the Machine Name field.
  10. Deploy the app to the Hololens by clicking Build -> Deploy Solution
  11. After deployment completes, open the Windows menu in the Hololens and select All Apps, and then click on the Angel_ARUI application.

ROS Unity Setup

ROS IP configuration

  1. In Unity, click Robotics -> ROS Settings to open the ROS Settings menu.
  2. Set the protocol to ROS2.
  3. Enter the IP address of the machine the TCP endpoint node will be running on (i.e. the machine the HoloLens 2 will be connecting to) and close the ROS Settings menu.

ROS message C# script generation

  1. In Unity, click Robotics -> Generate ROS Messages... to open the ROS Message Browser.
  2. Set the ROS message path to the directory containing the ROS2 messages for the project (../../ros/angel_msgs for this project's ANGEL message folder). The Message Browser should display the .msg files it found in the ROS message path.
  3. Click Build msgs and wait for message generation to finish. You should now see new files in the Built message path location (default location is unity/ARUI/Assets/RosMessages).
  4. Close the ROS Message Browser.

Running application without a development environment

See Unity README.md for instructions on creating an application package and installing it via the HoloLens 2 device portal.

Misc. notes

  • Research mode must be enabled in the HoloLens headset (see "Enabling Research Mode" section here https://docs.microsoft.com/en-us/windows/mixed-reality/develop/advanced-concepts/research-mode).
  • The first time you start your application on the HoloLens, you may have to allow camera/microphone access to the app. Click yes on the popups and then restart the application.
  • Due to issues accessing the depth and PV camera simultaneously, the HoloLens OS version should be less than 20348.1501. Version 20348.1432 has been tested with the app and confirmed to work. See this issue for more information. To install an older OS version on the HoloLens, follow the instructions here.
  • Although the short throw depth camera data provided by research mode is provided as UINT16 data, the max valid value is 4090 (values above 4090 signify an invalid reading from the camera). So, the true range of the short throw depth camera is [0, 4090].

ROS 2 System

ROS 2 Foxy is utilized to support our system of streaming analytics and report-back to the HoloLens2 platform.

Workspace root: ./ros/

System requirements

  • ansible
  • docker
  • docker-compose

Some files required from the https://data.kitware.com Girder service require authentication due to their protected nature. The environment variable GIRDER_API_KEY must be defined with a valid API key, otherwise an authentication token cannot be retrieved.

Provision Files

External large files should be provisioned by running the ansible tool:

ansible-playbook -i ansible/hosts.yml ansible/provision_files.yml

This may include large files for running the system, like ML model files, or other files required for building docker images.

This provisioning may require additional configuration and variables set in your environment in order to satisfy some permissions:

  • GIRDER_API_KEY will need to be set in order to acquire protected files from data.kitware.com.

The configuration that controls what is staged and where is located in the ansible/roles/provision-files/vars/main.yml file.

Docker-based Workflow

Intention: Use containerization to standardize development and runtime environment and practice.

  • Docker is utilized for containerization.
  • Docker-compose is used to manage container build and run
    configurations.

Docker functionality is located under the ./docker/ directory.

  • workspace-base-dev provides a base environment that supports building and running our workspace.
  • workspace-build provides a build of our workspace.

Building Docker Images

Run ./angel-docker-build.sh.

Developing within Docker

To develop adequately in docker, the container environment needs to have access to the source code that is being edited, likely by an IDE on the host. Running ./angel-workspace-shell.sh will create a temporary docker container and drop into a bash shell. This script has some usage output that can be seen by passing a -h/--help option. By default, the workspace-shell-dev-gpu service will be run. The definition of this service is found in the docker/docker-compose.yml configuration.

This will mount the ./ros/ subtree on the host system into the /angel_workspace/src/ directory in the run container.

This "workspace" context additionally mounts build, install and log output directories to a spot on the host in order to:

  • persist between shell start-ups and shutdowns
  • facilitate build sharing between multiple workspace shells

Due to this, there will not be a build available upon first shell start-up. The script /angel_workspace/workspace_build.sh is available to run. This script is used during the image build process, so using this script ensures that the same build method is performed.

Other directories and files are mounted into the container environment for development purposes and external file sharing.

This shell will NOT have the local installation sourced in order to facilitate further safe build actions. ros2 run actions should be performed in a separate shell from where builds are performed.

NOTE that any new system requirements may of course be installed locally, but these will be lost upon container shutdown.

  • Additional core requirements should be reflected in the ./docker/workspace-build/ image definition.
  • Changes to the workspace build process should be reflected in the ./docker/workspace-build/ image definition.
  • Additional development only dependencies should be added to the ./docker/workspace-base-dev image definition.

Container Cyclone DDS configuration

A basic template config may be auto-generated to specify which host network interface for it to use by uncommenting and setting the CYCLONE_DDS_INTERFACE in the docker/.env or exporting it on your commandline to the desired value.

Run Configurations -- Tmuxinator

The "standard" way to set up and run collections of nodes in ROS2 is via launch files. This is all well and good and provides great features, but what it doesn't do is provide access to individual components at runtime. During development, and often in the field as well, it is important to be able to get at individual components to see what might be going wrong or to restart/tweak one thing without impacting everything else that is running. We utilize tmux, configured and run by tmuxinator, to manage multiple windows/panes to host individual components.

Tmuxinator configurations are stored in the ./tmux/ directory.

Example: Object detection system fragment

./angel-workspace-shell.sh -r -- tmuxinator start fragment_object_detection_debug

Anatomy of the call:

  1. (Re)uses angel-workspace-shell.sh to run a command in a docker container.
  2. -r option to script sets "use our built workspace" flag.
  3. Things to the right of -- are run inside the container.
  4. tmux directory is (by default) in the same directory as the working directory the container starts in.
  5. tmuxinator command creates a new server session defined by the given config.

To stop the system after using the above command, we simply need to exit the tmux instance or kill the tmux session. This can be done by providing the tmux keyboard command <Ctrl-B, D>. Alternatively, in a new or existing pane, running tmux kill-session or tmux kill-server. When using the above example "start" command, exiting the tmux session will also shut down the container.

If starting an angel-workspace-shell.sh -r first, dropping into a bash terminal, and then calling tmuxinator start fragment_object_detection_debug, we have the option to exit the tmux session and stop it using another tmuxinator command:

tmuxinator stop fragment_object_detection_debug

Configuring ROS nodes that utilize SMQTK-Core

Some ROS nodes utilize the smqtk-core plugin system so specification of what algorithm is utilized is determined based on a configuration file.

Configuration files are currently located in: ros/angel_system_nodes/configs/

  • default_object_det_config.json
    • Determines the image object detection plugin used in the angel_system_nodes object_detector.py node.
  • default_activity_det_config.json
    • Determines the activity detection plugin used in the angel_system_nodes activity_detector.py node.

Setting up the foot pedal for annotations

The annotation_event_monitor ROS node uses the up and down arrow keys to generate AnnotationEvent messages. These messages can be used to determine when the beginning and end of an activity or error occur during a recording.

To help with this process, a foot pedal can be used to map foot pedal presses to keyboard presses. For this system, we are using the Infinity 3 USB foot pedal.

To configure your Linux system to recognize foot pedal presses as keyboard presses, see this guide.

In the .hwdb file, make sure to map the keyboard presses to the up and down arrow keys.

ANGEL System Python Package

angel_system/ contains the interfaces and implementations for the various components in the ANGEL system python package.

Running PTG evaluation

See angel_system/eval/README.md for details.

Lessons Learned

rosdep

References to the lists that rosdep uses to resolve names: /etc/ros/rosdep/sources.list.d/20-default.list

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