RMF Demos

The Open Robotics Middleware Framework (Open-RMF) enables interoperability among heterogeneous robot fleets while managing robot traffic that share resources such as space, building infrastructure systems (lifts, doors, etc) and other automation systems within the same facility. Open-RMF also handles task allocation and conflict resolution among its participants (de-conflicting traffic lanes and other resources). These capabilities are provided by various libraries in Open-RMF. For more details about Open RMF, refer to the comprehensive documentation provided here.

This repository contains demonstrations of the above mentioned capabilities of RMF. It serves as a starting point for working and integrating with Open-RMF.

(Click to watch video)

System Requirements

These demos were built and tested on

• Ubuntu 24.04 LTS

• ROS 2 - Jazzy

• Gazebo Harmonic

  Note: RMF is fully supported on ROS 2 Humble and Iron as well, but those will require ros_gz to be built from source.

Installation

Instructions can be found here.

FAQ

Answers to frequently asked questions can be found here.

Roadmap

A near-term roadmap of the Open-RMF project can be found in the user manual here.

RMF-Web quick start

Full web application of Open-RMF: rmf-web.

Start the backend API server via docker with host network access, using the default configuration. The API server will be accessible at localhost:8000 by default.

docker run \
  --network host \
  -it \
  -e ROS_DOMAIN_ID=<ROS_DOMAIN_ID> \
  -e RMW_IMPLEMENTATION=<RMW_IMPLEMENTATION> \
  ghcr.io/open-rmf/rmf-web/api-server:latest

Note: The API server is also configurable by mounting the configuration file and setting the environment variable RMF_API_SERVER_CONFIG. In the default configuration, the API serer will use an internal non-persistent database.

Start the frontend dashboard via docker with host network access, using the default configuration. The dashboard will be accessible at localhost:3000 by default.

docker run \
  --network host \
  -it \
  ghcr.io/open-rmf/rmf-web/dashboard:latest

Note: The dashboard via docker is not runtime-configurable and is best used for quick integrations and testing. To configure the dashboard, check out rmf-web-dashboard-resources and the dashboard configuration section.

In order to interact with the default configuration of the web application, the server_uri launch parameter will need to be changed to ws://localhost:8000/_internal, for example,

ros2 launch rmf_demos_gz office.launch.xml server_uri:="ws://localhost:8000/_internal"

By specifying server_uri, the fleetadapter will update rmf-web api-server with the latest task and robot states. User can then monitor on-going states and initiate rmf task with an interactive web dashboard.

Demo Worlds

• Hotel World
• Office World
• Airport Terminal World
• Clinic World
• Campus World
• Manufacturing & Logistics World

Hotel World

This hotel world consists of a lobby and 2 guest levels. The hotel has two lifts, multiple doors and 3 robot fleets (4 robots). This demonstrates an integration of multiple fleets of robots with varying capabilities working together in a multi-level building.

Demo Scenario

To launch the world and the schedule visualizer,

source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos_gz hotel.launch.xml

# Or, run with ignition simulator
ros2 launch rmf_demos_gz hotel.launch.xml

Here, we will showcase 2 types of Tasks: Loop and Clean, you can dispatch them via CLI as follows:

ros2 run rmf_demos_tasks dispatch_patrol -p restaurant  L3_master_suite -n 1 --use_sim_time
ros2 run rmf_demos_tasks dispatch_clean -cs clean_lobby --use_sim_time

Robots running Clean and Loop Task:

Office World

An indoor office environment for robots to navigate around. It includes a beverage dispensing station, controllable doors and laneways which are integrated into RMF.

source ~/rmf_demos_ws/install/setup.bash
ros2 launch rmf_demos_gz office.launch.xml

# Or, run with ignition simulator
ros2 launch rmf_demos_gz office.launch.xml

Now we will showcase 2 types of Tasks: Delivery and Loop

You can request the robot to deliver a can of coke from pantry to hardware_2 through the following:

ros2 run rmf_demos_tasks dispatch_delivery -p pantry -ph coke_dispenser -d hardware_2 -dh coke_ingestor --use_sim_time

You can also request the robot to move back and forth between coe and lounge through the following:

ros2 run rmf_demos_tasks dispatch_patrol -p coe lounge -n 3 --use_sim_time

The office demo can be run in secure mode using ROS 2 DDS-Security integration. Click here to learn more.

Airport Terminal World

This demo world shows robot interaction on a much larger map, with a lot more lanes, destinations, robots and possible interactions between robots from different fleets, robots and infrastructure, as well as robots and users. In the illustrations below, from top to bottom we have how the world looks like in traffic_editor, the schedule visualizer in rviz, and the full simulation in gazebo,

Demo Scenario

In the airport world, we introduce a new task type to rmf: Clean. To launch the world:

source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos_gz airport_terminal.launch.xml

You can submit loop, delivery or clean task via CLI:

ros2 run rmf_demos_tasks dispatch_patrol -p s07 n12 -n 3 --use_sim_time
ros2 run rmf_demos_tasks dispatch_delivery -p mopcart_pickup -ph mopcart_dispenser -d spill -dh mopcart_collector --use_sim_time
ros2 run rmf_demos_tasks dispatch_clean -cs zone_3 --use_sim_time

To see crowd simulation in action, enable crowd sim by:

ros2 launch rmf_demos_gz airport_terminal.launch.xml use_crowdsim:=1

Non-autonomous vehicles can also be integrated with Open-RMF provided their positions can be localized in the world. This may be of value at facilities where space is shared by autonomous robots as well as manually operated vehicles such as forklifts or transporters. In this demo, we can introduce a vehicle (caddy) which can be driven around through keyboard/joystick teleop. In Open-RMF nomenclature, this vehicle is classified as a read_only type, ie, Open-RMF can only infer its position in the world but does not have control over its motion. Here, the goal is to have other controllable robots avoid this vehicle’s path by replanning their routes if needed. The model is fitted with a plugin which generates a prediction of the vehicle’s path based on its current heading. It is configured to occupy the same lanes as the tinyRobot robots. Here, a read_only_fleet_adapter submits the prediction from the plugin to the Open-RMF schedule.

In the airport terminal map, a Caddy is spawned in the far right corner and can be controlled with geometry_msgs/Twist messages published over the cmd_vel topic.

Run teleop_twist_keyboard to control the caddy with your keyboard:

# Default launch with gazebo
ros2 run teleop_twist_keyboard teleop_twist_keyboard

ros2 launch rmf_demos_gz airport_terminal_caddy.launch.xml

Clinic World

This is a clinic world with two levels and two lifts for the robots. Two different robot fleets with different roles navigate across two levels by lifts. In the illustrations below, we have the view of level 1 in traffic_editor (top left), the schedule visualizer in rviz (right), and the full simulation in gazebo (bottom left).

Demo Scenario

To launch the world and the schedule visualizer,

source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos_gz clinic.launch.xml

You can submit tasks via CLI:

ros2 run rmf_demos_tasks dispatch_patrol -p L1_left_nurse_center L2_right_nurse_center -n 5 --use_sim_time
ros2 run rmf_demos_tasks dispatch_patrol -p L2_north_counter L1_right_nurse_center -n 5 --use_sim_time

Robots taking lift:

Multi-fleet demo:

Campus World

This is a larger scale “Campus” World. In this world, there are multiple delivery robots that operate. The world is designed and traffic lanes are annotated at the planet scale, using GPS WGS84 coordinates. Each robot is also streaming its location in WGS84 coordinates, which are processed by its fleet adapter. This demo intends to show the potential of Open-RMF on a large scale map.

Demo Scenario

To launch the world and the schedule visualizer,

source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos_gz campus.launch.xml

ros2 run rmf_demos_tasks  dispatch_patrol -p room_5 campus_4 -n 10 --use_sim_time
ros2 run rmf_demos_tasks  dispatch_patrol -p campus_5 room_3 -n 10 --use_sim_time
ros2 run rmf_demos_tasks  dispatch_patrol -p room_2 dead_end -n 10 --use_sim_time

RobotManager Integration

fleet_robotmanager_mqtt_bridge (see rmf_demos_bridges) can be used to publish robot locations, battery percentage and state to a /robot/status/ROBOT-ID websocket endpoint. An instance of RobotManager can be configured to subscribe to this server to receive json messages, which will in turn visualize the robots on RobotManager.

# Install the prerequisites
sudo apt install mosquitto mosquitto-clients

# Start the bridge
ros2 run rmf_demos_bridges fleet_robotmanager_mqtt_bridge -y 31500 -x 22000

The json messages for the first robot can be echoed using the following example command,

mosquitto_sub -t /robot/status/00000000-0000-0000-0000-000000000001

Manufacturing & Logistics World

An Open-RMF simulation demonstration created by ROS-Industrial Asia Pacific showcasing workcell (conveyor and fixed manipulator), multiple AMR fleets and infrastructure interoperability using the Open Robotics Middleeware Framework (Open-RMF).

[](https://www.youtube.com/watch?v=oSVQrjx_4w4)

Other Tools and Features Demos

• Traffic Light Robot Demos
• Additional Features
• Task Dispatching in Open-RMF

Traffic Light Robot Demos

Open-RMF can also manage fleets whose API or fleet managers only offer pause and resume commands to control their robots. Such fleets are classified as traffic_light. To integrate a traffic_light fleet, users are expected to implement a traffic_light fleet adapter based on this API. The rmf_demos repository contains demonstrations of traffic_light fleets in various scenarios. A simplistic mock_traffic_light adapter is used in these demonstrations.

Triple-H scenario:

$ ros2 launch rmf_demos_gz triple_H.launch.xml
(new terminal) $ ros2 launch rmf_demos the_pedigree.launch.xml

Battle Royale Scenario:

$ ros2 launch rmf_demos_gz battle_royale.launch.xml
(new terminal) $ ros2 launch rmf_demos battle_go.launch.xml

Office Scenario:

Note that tinyRobot1 is a standard “full control” robot, while tinyRobot2 “traffic light” robot.

$ ros2 launch rmf_demos_gz office_mock_traffic_light.launch.xml
(new terminal) $ ros2 launch rmf_demos office_traffic_light_test.launch.xml

Additional Features

• Flexible Tasks Scripts For more details.

• lift watchdog

  • The robot can query an external lift_watchdog_server for the permission to enter the lift cabin during the LiftSession Phase.
  • Command lines:

    # run hotel world with lift_watch_dog enabled
    ros2 launch rmf_demos_gz hotel.launch.xml enable_experimental_lift_watchdog:=1

    ## On a separate terminal, set lift as crowded
    ros2 launch rmf_demos experimental_crowded_lift.launch.xml

    # Dispatch robot from level1 to level3, robot will wait in front of the lift cabin
    ros2 run rmf_demos_tasks dispatch_patrol -p L3_room1  L3_room1 -n 1 --use_sim_time

    # Lift is cleared. Give robot the permission to enter the lift
    ros2 launch rmf_demos experimental_clear_lift.launch.xml
    

• Custom Docking Sequence
  • Fleet adapter will notify the robot (via dock() api/ModeRequest) to execute its custom dock sequence when the robot reaches a “dock” waypoint.
  • Implementation is similar to Clean task, refer to docs here
• Emergency Alarm
  • All robots will get directed to the nearest parking spot when the emergency alarm is triggered.
  • Command lines:

    # toggle alarm ON
    ros2 topic pub -1 /fire_alarm_trigger std_msgs/Bool '{data: true}'

    # toggle alarm OFF
    ros2 topic pub -1 /fire_alarm_trigger std_msgs/Bool '{data: false}'
    

Task Dispatching in Open-RMF

In Open-RMF version 21.04 and above, tasks are awarded to robot fleets based on the outcome of a bidding process that is orchestrated by a Dispatcher node, rmf_dispatcher_node. When the Dispatcher receives a new task request from a UI, it sends out a rmf_task_msgs/BidNotice message to all the fleet adapters. If a fleet adapter is able to process that request, it submits a rmf_task_msgs/BidProposal message back to the Dispatcher with a cost to accommodate the task. An instance of rmf_task::agv::TaskPlanner is used by the fleet adapters to determine how best to accommodate the new request. The Dispatcher compares all the BidProposals received and then submits a rmf_task_msgs/DispatchRequest message with the fleet name of the robot that the bid is awarded to. There are a couple different ways the Dispatcher evaluates the proposals such as fastest to finish, lowest cost, etc which can be configured.

Battery recharging is tightly integrated with the new task planner. ChargeBattery tasks are optimally injected into a robot’s schedule when the robot has insufficient charge to fulfill a series of tasks. Currently we assume each robot in the map has a dedicated charging location as annotated with the is_charger option in the traffic editor map.

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