# faster **Repository Path**: ycd/faster ## Basic Information - **Project Name**: faster - **Description**: IEEE IROS 2019，最新无人机飞控算法，在未知环境下的无人机快速安全航迹规划 - **Primary Language**: Unknown - **License**: BSD-3-Clause - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 1 - **Created**: 2021-10-19 - **Last Updated**: 2025-09-21 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments # **Finalist to the Best Paper Award on Safety, Security, and Rescue Robotics (IROS 2019)** UAV | Ground Robot | :-------------------------:|:-------------------------:| [![IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments](./faster/imgs/uav_sim.gif)](https://www.youtube.com/watch?v=fkkkgomkX10 "IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments") | [![IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments](./faster/imgs/gr_sim.gif)](https://youtu.be/L13k44-krcc "IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments") | [![IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments](./faster/imgs/uav_hw.gif)](https://www.youtube.com/watch?v=fkkkgomkX10 "IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments") | [![IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments](./faster/imgs/gr_hw.gif)](https://www.youtube.com/watch?v=fkkkgomkX10 "IROS 2019: FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments") | ## Citation When using FASTER, please cite this paper ([conference version](https://arxiv.org/abs/1903.03558), [journal version](https://arxiv.org/abs/2001.04420), [video](https://www.youtube.com/watch?v=gwV0YRs5IWs)): ```bibtex @inproceedings{tordesillas2019faster, title={{FASTER}: Fast and Safe Trajectory Planner for Flights in Unknown Environments}, author={Tordesillas, Jesus and Lopez, Brett T and How, Jonathan P}, booktitle={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year={2019}, organization={IEEE} } ``` ## General Setup FASTER has been tested with * Ubuntu 16.04/ROS Kinetic * Ubuntu 18.04/ROS Melodic Other ROS versions may require some minor changes, feel free to [create an issue](https://github.com/mit-acl/faster/issues) if you have any problems. The Gurobi versions tested are Gurobi 8.1, Gurobi 9.0, and Gurobi 9.1. Install the [Gurobi Optimizer](https://www.gurobi.com/products/gurobi-optimizer/). You can test your installation typing `gurobi.sh` in the terminal. Have a look at [this section](#issues-when-installing-gurobi) if you have any issues. Install the following dependencies: ``` sudo apt-get install ros-"${ROS_DISTRO}"-gazebo-ros-pkgs ros-"${ROS_DISTRO}"-mavros-msgs ros-"${ROS_DISTRO}"-tf2-sensor-msgs ``` ``` python -m pip install pyquaternion ``` Create a workspace, and clone this repo and its dependencies: ``` mkdir ws && cd ws && mkdir src && cd src git clone https://github.com/mit-acl/faster.git wstool init wstool merge ./faster/faster/install/faster.rosinstall ``` In the following, remember (once the workspace is compiled) to add this to your `~/.bashrc`: ``` source PATH_TO_YOUR_WS/devel/setup.bash ``` ### Instructions to use FASTER with an aerial robot: Compile the code: ``` wstool update -j8 cd .. catkin config -DCMAKE_BUILD_TYPE=Release catkin build ``` And finally open 5 terminals and execute these commands: ``` roslaunch acl_sim start_world.launch roslaunch acl_sim perfect_tracker_and_sim.launch roslaunch global_mapper_ros global_mapper_node.launch roslaunch faster faster_interface.launch roslaunch faster faster.launch ``` The blue grid shown in Rviz is the unknown space and the orange one is the occupied-known space. Now you can click `Start` in the GUI, and then, in RVIZ, press `G` (or click the option `2D Nav Goal` on the top bar of RVIZ) and click any goal for the drone. ### Instructions to use FASTER with a ground robot: > **_NOTE:_** There are some differences in the performance of the ground robot when using the Gazebo version that comes with ROS Kinetic and the one that comes with ROS Melodic. To achieve a good tracking error (like the one shown [here](https://github.com/mit-acl/faster/blob/master/faster/imgs/gr_sim.gif)), you may have to tune the [gains of the controller](https://github.com/mit-acl/faster/blob/master/faster/scripts/goal_odom_to_cmd_vel_state.py) depending on the specific verion of ROS/Gazebo that you are using. Install the following dependencies: ``` sudo apt-get install ros-"${ROS_DISTRO}"-control-toolbox ros-"${ROS_DISTRO}"-ros-control ros-"${ROS_DISTRO}"-robot-localization ros-"${ROS_DISTRO}"-lms1xx ros-"${ROS_DISTRO}"-interactive-marker-twist-server ros-"${ROS_DISTRO}"-hector-gazebo-plugins ros-"${ROS_DISTRO}"-move-base ros-"${ROS_DISTRO}"-ros-control ros-"${ROS_DISTRO}"-ros-controllers ros-"${ROS_DISTRO}"-pointgrey-camera-description ros-"${ROS_DISTRO}"-hardware-interface ros-"${ROS_DISTRO}"-message-to-tf ros-"${ROS_DISTRO}"-gazebo-ros-control ``` Then download the ground_robot-specific packages and compile the repo: ``` wstool merge ./faster/faster/install/faster_ground_robot.rosinstall wstool update -j8 cd .. catkin config -DCMAKE_BUILD_TYPE=Release catkin build ``` Then, in [`faster.yaml`](https://github.com/mit-acl/faster/tree/master/faster/param), change these parameters: ``` drone_radius: 0.5 #[m] z_max: 0.5 #[m] v_max: 1.4 #[m/s] a_max: 1.4 #[m/s2] j_max: 5.0 #[m/s3] is_ground_robot: true ``` And finally open 4 terminals and execute these commands ``` roslaunch faster ground_robot.launch roslaunch global_mapper_ros global_mapper_node.launch quad:=JA01 roslaunch faster faster_interface.launch quad:=JA01 is_ground_robot:=true roslaunch faster faster.launch quad:=JA01 ``` Now you can click `Start` in the GUI, and then, in RVIZ, press `G` (or click the option `2D Nav Goal` on the top bar of RVIZ) and click any goal for the ground robot. ## Architecture: ![](./faster/imgs/diagram.png) For the aerial robot, the option 3 is provided (a perfect tracker and a Gazebo simulation to obtain the depth). To make the simulation faster, the physics engine of Gazebo is disabled using [`disable_physics.cpp`](https://gitlab.com/mit-acl/lab/acl-gazebo/-/blob/master/acl_sim/src/disable_physics.cpp) of [`acl-gazebo`](https://gitlab.com/mit-acl/lab/acl-gazebo). For the ground robot, the option 2 is provided (a controller, and a Gazebo simulation with both dynamics and depth (using the `multi_jackal` package) ## How do I use FASTER with a real robot? To run the mapper, you simply need to run the node that publishes the depth image of the camera (for example using [`realsense-ros`](https://github.com/IntelRealSense/realsense-ros) if you are using an Intel RealSense camera). After launching this node, find the name of the topic of the depth image (by doing `rostopic echo`), and finally put that name on the [launch file of the mapper](https://gitlab.com/mit-acl/lab/acl-mapping/-/blob/dev/global-mapper/global_mapper_ros/launch/global_mapper_node.launch#L12). As shown in the diagram above, the UAV should subscribe to the [Goal message](https://gitlab.com/mit-acl/fsw/snap-stack/snapstack_msgs/-/blob/46a1911faed1a5b1be479df2f969ee4e17304f29/msg/QuadGoal.msg) published by FASTER. The estimator (or the motion capture) should then publish the current state of the UAV as a [State message](https://gitlab.com/mit-acl/fsw/snap-stack/snapstack_msgs/-/blob/master/msg/State.msg). If you are using a ground robot, you need to publish a [nav_msgs/Odometry message](http://docs.ros.org/en/api/nav_msgs/html/msg/Odometry.html) (see [this](https://github.com/mit-acl/faster/blob/1baccf08908ad5a049c9e3315e577b35214ce763/faster/scripts/goal_odom_to_cmd_vel_state.py#L218)), and it will be converted directly to a [State message](https://gitlab.com/mit-acl/fsw/snap-stack/snapstack_msgs/-/blob/master/msg/State.msg). ## Credits: This package uses code from the [JPS3D](https://github.com/KumarRobotics/jps3d) and [DecompROS](https://github.com/sikang/DecompROS) repos (included in the `thirdparty` folder), so credit to them as well. ## Issues when installing Gurobi: If you find the error: ``` “gurobi_continuous.cpp:(.text.startup+0x74): undefined reference to `GRBModel::set(GRB_StringAttr, std::__cxx11::basic_string, std::allocator > const&)'” ``` The solution is: ```bash cd /opt/gurobi800/linux64/src/build #Note that the name of the folder gurobi800 changes according to the Gurobi version sudo make sudo cp libgurobi_c++.a ../../lib/ ``` ## Issues with other possible errors: You can safely ignore these terminal errors: * `Error in REST request` (when using ROS Melodic) * `[ERROR] [...]: GazeboRosControlPlugin missing while using DefaultRobotHWSim, defaults to true.` (when using the ground robot) * `[ERROR] [...]: No p gain specified for pid. Namespace: /gazebo_ros_control/pid_gains/front_left_wheel.` (when using the ground robot)