MAV planning tools using voxblox as the map representation.
NOTE: THIS PACKAGE IS UNDER ACTIVE DEVELOPMENT! Things are subject to change at any time.
- Global Planning
- RRT*, RRT Connect, BIT*, PRM... (OMPL interface)
voxblox_rrt_planner
- Planning on skeleton sparse graphs
voxblox_skeleton_planner
- Skeleton sparse graphs (topology) generation from ESDF voxblox maps
voxblox_skeleton
- Randomized benchmark on a variety of real maps
mav_planning_benchmark
- RRT*, RRT Connect, BIT*, PRM... (OMPL interface)
- Path Smoothing (between waypoints)
- Velocity ramp
mav_path_smoothing
- Polynomial with adding additional vertices at collisions
mav_path_smoothing
- Local polynomial optimization (Loco), unconstraining waypoints and minimizing collisions
mav_path_smoothing, loco_planner
- Velocity ramp
- Local Planning --
mav_local_planner
- Interface to MAV controller, sending timed, dynamically feasible trajectories and replanning online
mav_local_planner
- Planning in a short horizon in unknown or partially unknown spaces, using trajectory optimization in ESDFs
voxblox_loco_planner
- Path smoothing between waypoints if all waypoints are in known free space
mav_path_smoothing
- Interface to MAV controller, sending timed, dynamically feasible trajectories and replanning online
- RVIZ Planning Plugin --
mav_planning_rviz
- Allows dragging around start and goal markers, sending planning requests to global planners
mav_planning_rviz
- Allows sending goal points either directly to controller or to the local planner
mav_local_planner
- Allows dragging around start and goal markers, sending planning requests to global planners
- Local Planning
- Improved goal selection
- Support for global and local coordinate frames
- RVIZ Planning Plugin
- Support for entering multiple waypoints
If using these, please cite:
voxblox
Helen Oleynikova, Zachary Taylor, Marius Fehr, Roland Siegwart, and Juan Nieto, “Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planning”. In IEEE Int. Conf. on Intelligent Robots and Systems (IROS), October 2017.
[pdf | bibtex | video | arxiv ]
loco planning
Helen Oleynikova, Michael Burri, Zachary Taylor, Juan Nieto, Roland Siegwart, and Enric Galceran, “Continuous-Time Trajectory Optimization for Online UAV Replanning”. In IEEE Int. Conf. on Intelligent Robots and Systems (IROS), October 2016.
[pdf | bibtex | video]
loco planning with voxblox
Helen Oleynikova, Zachary Taylor, Roland Siegwart, and Juan Nieto, “Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles”. IEEE Robotics and Automation Letters, 2018.
[pdf | bibtex | video | arxiv ]
voxblox skeleton and skeleton planning
Helen Oleynikova, Zachary Taylor, Roland Siegwart, and Juan Nieto, “Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning”. In IEEE Int. Conf. on Intelligent Robots and Systems (IROS), October 2018.
[pdf | bibtex | video | arxiv ]
This package is intended to be used with Ubuntu 16.04 and ROS kinetic or above. After installing ROS, install some extra dependencies, substituting kinetic for your ROS version as necessary:
sudo apt-get install ros-kinetic-cmake-modules python-wstool python-catkin-tools libyaml-cpp-dev protobuf-compiler autoconf
Then if not already done so, set up a new catkin workspace:
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws
catkin init
catkin config --extend /opt/ros/kinetic
catkin config --cmake-args -DCMAKE_BUILD_TYPE=Release
catkin config --merge-devel
If using SSH keys for github (recommended):
cd ~/catkin_ws/src/
git clone [email protected]:ethz-asl/mav_voxblox_planning.git
wstool init . ./mav_voxblox_planning/install/install_ssh.rosinstall
wstool update
If not using SSH keys but using https instead:
cd ~/catkin_ws/src/
git clone https://github.com/ethz-asl/mav_voxblox_planning.git
wstool init . ./mav_voxblox_planning/install/install_https.rosinstall
wstool update
If you have already initalized wstool replace the above wstool init
with wstool merge -t
Compile:
cd ~/catkin_ws/src/
catkin build mav_voxblox_planning
We've prepared a number of maps for you to try out our planning on. The archive is 260 MB big and available here.
It contains 6 maps from 3 scenarios: machine hall (indoor), shed (mixed indoor and outdoor area), and rubble (outdoor), each with Intel Realsense D400-series scans and with grayscale stereo matching scans. Each map features 3 files: esdf, skeleton (esdf + skeleton diagram), and sparse graph, which contains just the sparse graph generated using skeletonization.
Dataset | Realsense | Stereo |
---|---|---|
Machine Hall | ![]() |
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Rubble | ![]() |
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Shed | ![]() |
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Make sure all the packages have built successfully! Re-source your workspace (source ~/catkin_ws/devel/setup.bash
) and start up rviz (rviz
).
In rviz, select Panels -> Add New Panel
and select Planning Panel
:
Next, under Displays
, add an InteractiveMarkers
display with the topic /planning_markers/update
:
You should now see both a path panel and start and goal arrows. You can select Edit
on either the start or the goal to drag it around as an interactive marker:
You can also edit the numbers in the x, y, z, yaw fields manually; the markers and the numbers will update automatically to match.
In ~/catkin_ws/src/mav_voxblox_planning/voxblox_rrt_planner/launch/rrt_saved_map.launch
, open the file and replace the voxblox_path
to the path of one of the esdf maps you downloaded above.
Then run the file:
roslaunch voxblox_rrt_planner rrt_saved_map.launch
Note that the Fixed Frame
in RVIZ should match the value for the frame_id
parameter in the launch file, in this case map
. Using the another value for the Fixed Frame
will result in no mesh display.
In the planning panel, enter voxblox_rrt_planner
as the planner name, and add a VoxbloxMesh
display with the topic /voxblox_rrt_planner/mesh
and a MarkerArray
display with the topic /voxblox_rrt_planner/path
.
You can now press the "Planner Service" button to plan!
In green is the RRT output path, and the other colors show different types of smoothing through these waypoints.
Very similar to above... Open ~/catkin_ws/src/mav_voxblox_planning/voxblox_skeleton_planner/launch/skeleton_saved_map.launch
and update the paths to point to matching skeleton and sparse graph files from the maps above.
Run it with:
roslaunch voxblox_skeleton_planner skeleton_saved_map.launch
In the planning panel, enter voxblox_skeleton_planner
as the planner name, and add a VoxbloxMesh
display with the topic /voxblox_skeleton_planner/mesh
and a MarkerArray
display with the topic /voxblox_skeleton_planner/path
. Additionally you can add a MarkerArray
with topic /voxblox_skeleton_planner/sparse_graph
You can now press the "Planner Service" button to plan!
Pink is the shortened path from the sparse graph, and teal is smoothed using loco through it.
This demo is about using the mav_local_planner to do live replanning at 4 Hz in a simulation environment.
The local planner uses loco
to locally track a waypoint, or if given a list of waypoints, plan a smooth path through them.
Follow the installation instructions here to install Rotors Simulator, which is an MAV simulator built on top of gazebo. This will allow us to fully simulate a typical MAV, with a visual-inertial sensor mounted on it.
See instructions above: here.
After rotors is up and running, in a new terminal, launch the firefly sim:
roslaunch mav_local_planner firefly_sim.launch
A gazebo window will come up, showing something similar to this:
You can then control the MAV using the planning panel. Enter firefly
as the Namespace
in the planning panel, then either type a position for the goal or edit the goal to drag it around. To send it to the local planner, press the Send Waypoint
button.
The trajectory will be visualized as a visualization_msgs/MarkerArray
with the topic /firefly/mav_local_planner/local_path
and you can view the explored mesh as a voxblox_msgs/Mesh
message with the topic /firefly/voxblox_node/mesh
. The complete setup is shown below:
In case the MAV gets stuck, you can use Send to Controller
, which will directly send the pose command to the controller -- with no collision avoidance or trajectory planning.
Once you've explored some of the map in simulation, you can also use the global planner to plan longer paths through known space.
First, start the simulation global RRT* planner (this is in addition to the firefly_sim.launch
file above):
roslaunch voxblox_rrt_planner firefly_rrt.launch
Local planning only uses the goal point, but global planning requires a start point as well (as the global planner does not know the odometry of the MAV). For this, we can use the Set start to odom
option in the planning panel.
To do this, in the Odometry Topic
field, enter ground_truth/odometry
and check the Set start to odom
check-box. Now the start location will automatically track the odometry of the Firefly as it moves.
Once the start and goal poses are set as you want, press Planner Service
. In rviz, add a MarkerArray
display with the topic /firefly/voxblox_rrt_planner/path
to visualize what the planner has planned. Once you are happy with this path, press Publish Path
to send it to the local planner, which should start tracking the path immediately.
TODO! Instructions coming soon. See the voxblox_skeleton/launch/skeletonize_map.launch
file for reference, please make an issue if there are any questions or problems.