Integration and Supervisory control of Autonomous Robots
Project description
ISAR
ISAR - Integration and Supervisory control of Autonomous Robots - is a tool for integrating robot applications into operator systems. Through the ISAR API you can send commands to a robot to do missions and collect results from the missions.
Getting started
Steps:
- Install
- Integrate a robot
- Run the ISAR server
- Run a robot mission
Install
For local development, please fork the repository. Then, clone and install in the repository root folder:
git clone https://github.com/equinor/isar
cd isar
pip install -e .[dev]
For zsh you might have to type ".[dev]"
Verify that you can run the tests:
pytest .
Robot integration
To connect the state machine to a robot in a separate repository, it is required that the separate repository implements the robot interface. A mocked robot can be found in this repository. Install the repo, i.e:
pip install git+https://@github.com/equinor/isar-robot.git@main
Then, ensure the robot_package variable in default.ini
is set to the name of the package you installed. isar_robot is set by default.
If you have the robot repository locally, you can simply install through
pip install -e /path/to/robot/repo/
Running ISAR with a robot simulator
A simulator based on the open source robot Turtlebot3 has been implemented for use with ISAR and may be
found here. Follow the installation instructions for the simulator and
install isar-turtlebot in the same manner as given in the robot integration section. Set the
following configuration variables in default.ini:
robot_package = isar_turtlebot
default_map = turtleworld
Run ISAR server
To run ISAR:
python main.py
Note, running the full system requires that an implementation of a robot has been installed. See this section for installing a mocked robot or a Turtlebot3 simulator.
Running a robot mission
Once the application has been started the swagger site may be accessed at
http://localhost:3000/docs
Execute the /schedule/start-mission endpoint with mission_id=1 to run a mission.
In this folder there are predefined default missions, for example the mission
corresponding to mission_id=1. A new mission may be added by adding a new json-file with a mission description. Note,
the mission IDs must be unique.
Running tests
After following the steps in Development, you can run the tests:
pytest .
To create an interface test in your robot repository, use the function interface_test from robot_interface. The
argument should be an interface object from your robot specific implementation.
See isar-robot for example.
Integration tests
Integration tests can be found here and have been created
with a simulator in mind. The integration tests will not run as part of pytest . or as part of the CI/CD pipeline. To
run the integration tests please follow the instructions in this section for
setting up the isar-turtlebot implementation with simulator and run the following command once the simulation has been
launched.
pytest tests/integration
Note that these tests will run towards the actual simulation (you may monitor it through Gazebo and RVIZ) and it will take a long time.
Documentation
To build the project documentation, run the following commands:
cd docs
make docs
The documentation can now be viewed at docs/build/html/index.html.
Contributing
We welcome all kinds of contributions, including code, bug reports, issues, feature requests, and documentation. The preferred way of submitting a contribution is to either make an issue on GitHub or by forking the project on GitHub and making a pull requests.
Components
The system consists of two main components.
- State machine
- FastAPI
State machine
The state machine handles interaction with the robots API and monitors the execution of missions. It also enables interacting with the robot before, during and after missions.
The state machine is based on the transitions package for Python. The main states are:
- Idle: The robot is in an idle state and ready to perform new missions.
- Send: The state machine has received a mission and is sending the mission to the robot.
- Monitor: The robot has received a mission from the state machine, and the state machine is monitoring the current mission.
- Finalize: The state machine has finished the mission, received a request to abort, or an event has occurred which requires the mission to be canceled. Once finished the state machine will return to idle.
FastAPI
The FastAPI establishes an interface to the state machine for the user. As the API and state machine are separate threads, they communicate through python queues. FastAPI runs on an ASGI-server, specifically uvicorn. The FastAPI-framework is split into routers where the endpoint operations are defined.
Mission planner
The mission planner that is currently in use is defined by the mission_planner configuration variable. This can be set
in the default configuration. The available options are
mission_planner = local
mission_planner = echo
By default, the local planner is used.
Implement your own planner
You can create your own mission planner by implementing the mission planner interface and adding your planner to the selection here. Note that you must add your module as an option in the dictionary.
Storage
The storage modules that are used is defined by the storage configuration variable. This can be set in
the default configuration. It accepts a comma separated string and will use each
element in the list to retrieve the corresponding handler. The current options are
storage = local, blob, slimm
Note that the blob and slimm options require special configuration to authenticate to these endpoints.
Implement your own storage module
You can create your own storage module by implementing the storage interface and adding your storage module to the selection here. Note that you must add your module as an option in the dictionary.
API authentication
The API has an option to include user authentication. This can be set in the default configuration.
authentication_enabled = false
authentication_enabled = true
By default, the local storage module is used and API authentication is disabled. If using Azure Blob Storage a set of
environment variables must be available which gives access to an app registration that may use the storage account.
Enabling API authentication also requires the same environment variables. The required variables are
AZURE_CLIENT_ID
AZURE_TENANT_ID
AZURE_CLIENT_SECRET
MQTT communication
ISAR is able to publish parts of its internal state to topics on an MQTT broker whenever they change. This is by default turned off but may be activated by setting
mqtt_enabled = true
in default.ini. The connection to the broker will be determined by the following configuration values in default.ini.
mqtt_username
mqtt_host
mqtt_port
In addition, the MQTT_PASSWORD environment variable should be available for connection to the broker. If username and
password is not specified both will default to empty strings.
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