The tum_ar package provides a collection of tools for human-machine interfaces for manual and collaborative tasks in industrial manufacturing environments. It is meant for collaborative workspace equipped with a top-down projector.
It can be used to project instructions on static objects, as shown above, but also works with dynamic objects held by a robot's end effector.
- System components
The package consists of three major nodes:
The ar_server manages ar tasks. It receives new tasks as an tum_ar_msgs/ARTaskAction on the ar_task topic. It then feeds the ar_window with the individual projection slides and waits for a user feedback. The feedback can also be supplied by other sources, such as the touchscreen_window node.
Note that all nodes are launched within the /ar namespace by default.
The tum_ar component is entirely ROS based. It has been tested with ROS melodic and kinetic. On top of an existing ROS installtion (desktop full) the following packages need to be installed:
sudo apt install ros-melodic-rosapi libqt5svg5-dev
The system requires configuration parameters describing the projector, e.g.
- [2700, 0, 960]
- [ 0, 2700, 600]
- [ 0, 0, 1]
resolution: [1920, 1200]
A sample config file can be found in tum_ar_window/config/projector_tum.yaml. The projection matrix is equivalent to k matrix describing a camera using the pinhole model.
Once you created a new config file for your projector open the launch file at tum_ar_window/launch/ar_window.launch and change the line
<arg name="projector_config" default="$(find tum_ar_window)/config/projector_tum.yaml"/>
to include your yaml file instead, or provide a parameter accordingly.
To start projecting you need to launch the ar_server and ar_window by executing
roslaunch tum_ar_window ar.launch
Note that the AR window will launch in full screen mode. You can use the + keyboard shortcut to get back to your desktop. By right clicking on the windows entry in your task bar you can move it to another screen if required. You can now use the ar_task interface to show a set of instructions.
Defining AR Slides
All projections setups are speciqied as AR slides defined by the tum_ar_msgs/ARSlide message type. Each slide is composed of the following four types of definitions:
pois - A Point of Interest (POI) is a point to be highlighted be drawing a circle around it. It is defined by
- header - Header specifying the frame in which the POI is defined
- position - <x, y, z> position of the POI
- border_color - Color of the circle drawn around the POI
- fill_color - Fill color of the circle
- radius - Radius of the highlighted area in meters
- label - Optional label to be projected next to the POI
boxes - Similar to POIs it is possible to define rectangular areas to be highlighted:
- header - Header specifying the frame in which the box is defined
- position - <x, y, z> position of the box
- border_color - Color of the box's frame
- fill_color - Fill color of the box
- width - Width of the box
- height - Height of the box
- label - Optional label to be projected next to the box
- instruction - Instruction to be projected on close to the bottom of the projection area (see sample images in introduction)
outcomes - An array Define the possible outcomes of a task. Each slide has to be completed by an input selecting one of the possible outcomes)
- id - ID of the outcome state
- name - Name of the outcome state
- type - Type of the outcome state (TYPE_DEFAULT, TYPE_INFO, TYPE_SUCCESS, TYPE_WARN or TYPE_ERROR). This defines how the potential outcome is styled in the UI.
As the definition of slides can be time-consuming, it is also possible to define them in a file and just pass the path as a parameter. A sample file can be found at tum_ar_window/slides/example.yaml.
- Touchsreen Interface
The tum_touchscreen_ui package provides an additional interface, allowing the user to make inputs in a simple way. Similar to the ar_window node it receive the individual AR slides provided by the ar_server. However, it only displays the instruction as well as one button for each possible outcome.
- Demonstration scenarios
The system has successfully been demonstrated in two demonstrators of the HORSE project: In the pilot case at BOSCH Spain the system has been used to highlight potential defects on WSA motor, confirm and train the decisions of an machine learning based, automated vision system.
Besides, the system is part of the HORSE technology demonstrator installed at the HORSE CC at Technical University of Munich. In this second demonstrator the AR system supports an ongoing collaboration between a human operator and a robot. Τhe projector is used to highlight the initial object poses during preparation, highlights two inspection points during the robots pick and place task and finally gives introductions on how to complete the task by removing the filled box and/or the rejected objects.
- Download information
The system is publicly available for download under https://github.com/TUM-I6/tum_ar