The Robotics Middleware Framework (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. 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 RMF.
This repository contains demonstrations of the above mentioned capabilities of RMF. It serves as a starting point for working and integrating with RMF.
These demos were developed and tested on
Instructions can be found here.
Answers to frequently asked questions can be found here.
A near-term roadmap of the RMF project can be found in the user manual here.
The RMF panel is a web based dashboard for interacting with RMF. It allows users to send task requests to RMF and monitor the status of robots and submitted tasks. There are two main modes of submitting tasks to RMF via the Panel:
- Submit a Task: Used to submit a single task. The user is required to first select a request type from the drop down menu. Depending on the type selected, additional fields specify to the type will need to be populated. The user can then specify the
start timefor the task before clickingSubmit Request. - Submit a List of Tasks: Used to submit a batch of tasks. A
.jsonfile containing a list of tasks may be loaded via theChoose filebutton. Some example files are found inrmf_demos_panel/task_lists. Once loaded, clicking theSubmit Task Listbutton will automatically assign the various tasks to available robots.
Users may switch between different tabs on the top-left corner of the Panel when running the relevant demo world. More information on configuring the panel can be found here
Note: When running the demos on Ubuntu 18.04 (not officially supported), you are required to explicitly supply gazebo_version launch argument. Eg: ros2 launch rmf_demos office.launch.xml gazebo_version:=9
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 office.launch.xmlTo send task requests, open RMF Panel from a browser
firefox localhost:5000To submit a delivery task, select Delivery from the Select a request type dropdown list. Next, select coke from the Select delivery task list. Choose an desired start time for task and click submit.
Or, submit a task via CLI:
ros2 run rmf_demos_tasks dispatch_loop -s coe -f lounge -n 3 --use_sim_time
ros2 run rmf_demos_tasks dispatch_delivery -p pantry -pd coke_dispenser -d hardware_2 -di coke_ingestor --use_sim_time
To send loop requests, select Loop from the Select a request type dropdown list. Choose desired start and end locations and click submit.
To run a scenario with multiple task requests, load office_tasks.json from rmf_demos_panel/task_lists in the Submit a list of tasks section. This should populate the preview window with a list of tasks. Click submit and watch the demonstration unfold.
The office demo can be run in secure mode using ROS 2 DDS-Security integration. Click here to learn more.
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,
To launch the world and the schedule visualizer,
source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos airport_terminal.launch.xmlSelect the airport tab on RMF Panel. Load the airport_terminal_tasks.json list and click submit to begin a collection of loop, delivery and cleaning tasks.
Or, submit loop, delivery or clean task via CLI:
ros2 run rmf_demos_tasks dispatch_loop -s s07 -f n12 -n 3 --use_sim_time
ros2 run rmf_demos_tasks dispatch_delivery -p mopcart_pickup -pd mopcart_dispenser -d spill -di mopcart_collector --use_sim_time
ros2 run rmf_demos_tasks dispatch_clean -cs zone_3 --use_sim_timeTo see crowd simulation in action, enable crowd sim by:
ros2 launch rmf_demos airport_terminal.launch.xml use_crowdsim:=1Non-autonomous vehicles can also be integrated with 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 RMF nomenclature, this vehicle is classified as a read_only type, ie, 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 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
# if launch with use_ignition:=1
ros2 launch rmf_demos airport_terminal_caddy_ign.launch.xml
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).
To launch the world and the schedule visualizer,
source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos clinic.launch.xmlSelect the clinic tab on RMF Panel. Load the clinic_tasks.json list and click submit to begin a collection of loop and delivery tasks.
Or, submit a task via CLI:
ros2 run rmf_demos_tasks dispatch_loop -s L1_left_nurse_center -f L2_right_nurse_center -n 5 --use_sim_time
ros2 run rmf_demos_tasks dispatch_loop -s L2_north_counter -f L1_right_nurse_center -n 5 --use_sim_timeRobots taking lift:
Multi-fleet demo:
This is a hotel with a lobby and a guest level. The hotel has two lifts and two robot fleets. The tiny robots are supposed to guide the guests and the delivery robots are used to load and deliver cargo.
The hotel map is truncated due to the high memory usage. The full map can be accessed here.
Hotel floor plan in traffic_editor:
Full hotel floor plan in traffic_editor:
To launch the world and the schedule visualizer,
source ~/rmf_ws/install/setup.bash
ros2 launch rmf_demos hotel.launch.xmlSelect the hotel tab on RMF Panel. Loop requests can be submitted via "Submit a Task" form.
Robot taking lift:
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.
$ ros2 launch rmf_demos triple_H.launch.xml
(new terminal) $ ros2 launch rmf_demos the_pedigree.launch.xml$ ros2 launch rmf_demos battle_royale.launch.xml
(new terminal) $ ros2 launch rmf_demos battle_go.launch.xmlNote that tinyRobot1 is a standard "full control" robot, while tinyRobot2 "traffic light" robot.
$ ros2 launch rmf_demos office_mock_traffic_light.launch.xml
(new terminal) $ ros2 launch rmf_demos office_traffic_light_test.launch.xml
In 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.