# Fast-Planner

**Repository Path**: chenqianbang/Fast-Planner

## Basic Information

- **Project Name**: Fast-Planner
- **Description**: Package for the paper "Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight" 
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-12-12
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Fast-Planner

__Fast-Planner__ is a quadrotor trajectory generator for fast autonomous flight. It consists of 
the front-end _kinodynamic path searching_, the back-end _gradient-based Bspline trajectory optimization_ and the postprocessing named as _iterative time adjustment_. The key features of the planner are that it generates
high-quality trajectories within a few milliseconds and that it can generate aggressive motion under the premise of dynamic feasibility. This work was reported on the [IEEE Spectrum](https://spectrum.ieee.org/automaton/robotics/robotics-hardware/video-friday-nasa-lemur-robot).

This package is under active maintenance. More features (e.g., avoiding dynamic obstacles, discovering topological distinctive trajectories) will be added in the future.

__Authors__: [Boyu Zhou](http://boyuzhou.net), [Fei Gao](https://ustfei.com/) and [Shaojie Shen](http://uav.ust.hk/group/) from the [HUKST Aerial Robotics Group](http://uav.ust.hk/).

__Video__:

<!-- add some gif of the paper video: -->
<p align="center">
  <img src="img/exp1.gif" width = "420" height = "237"/>
<!-- </p> -->

<!-- <p align="center"> -->
  <img src="img/exp2.gif" width = "420" height = "237"/>
</p>

<p align="center">
  <a href="https://youtu.be/XxBw2nmL8t0" target="_blank"><img src="img/title.png" alt="video" width="480" height="270" border="1" /></a>
</p>

This package contains the implementation of __Fast-Planner__ (in folder __dyn_planner__) and a lightweight
quadrotor simulator (in __uav_simulator__).

If you use __Fast-Planner__ for your application or research, please cite our related papers:

- [__Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight__](https://ieeexplore.ieee.org/document/8758904), Boyu Zhou, Fei Gao, Luqi Wang, Chuhao Liu and Shaojie Shen, IEEE Robotics and Automation Letters (RA-L), 2019.
```
@article{zhou2019robust,
  title={Robust and efficient quadrotor trajectory generation for fast autonomous flight},
  author={Zhou, Boyu and Gao, Fei and Wang, Luqi and Liu, Chuhao and Shen, Shaojie},
  journal={IEEE Robotics and Automation Letters},
  volume={4},
  number={4},
  pages={3529--3536},
  year={2019},
  publisher={IEEE}
}
```

## 1. Prerequisites

- Our software is developed in Ubuntu 16.04, [ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu).

- We use [**NLopt**](https://nlopt.readthedocs.io/en/latest/NLopt_Installation) to solve the non-linear optimization problem.

- The drone simulator depends on the C++ linear algebra library __Armadillo__, which can be installed by ``` sudo apt-get install libarmadillo-dev ```.

## 2. Build on ROS

Clone this repository to your catkin workspace and catkin_make. A new workspace is recommended:
```
  cd ${YOUR_WORKSPACE_PATH}/src
  git clone https://github.com/HKUST-Aerial-Robotics/Fast-Planner.git
  cd ../
  catkin_make
```

## 3. Run the Simulation

Run [Rviz](http://wiki.ros.org/rviz) with our configuration firstly:

```
  <!-- go to your workspace and run: -->
  source devel/setup.bash
  roslaunch plan_manage rviz.launch
```

Then run the quadrotor simulator and __Fast-Planner__:

```
  <!-- open a new terminal, go to your workspace and run: -->
  source devel/setup.bash
  roslaunch plan_manage simulation.launch
```

Normally, you will find the randomly generated map and the drone model in ```Rviz```. At this time, you can select a goal for the drone using the ```3D Nav Goal``` tool.

In the tools panel of Rviz, click '+' and select the plugin 'Goal3DTool'. If you have successfully compiled all packages from __uav_simulator__, now you can see '3D Nav Goal' in the tools panel. To set a goal, click the '3D Nav Goal' (shortcut keyboard 'g', may conflict with 2D Nav Goal). Then __click__ and __hold__ both the left and right mouse buttons to select _(x,y)_, and __move__ the mouse to change _z_. When a goal is set successfully, a new trajectory will be generated immediately and executed by the drone, as displayed below:

<!-- add some gif here -->
 <p align="center">
  <img src="img/exp3.gif" width = "640" height = "360"/>
 </p>

## 4. Acknowledgements
  We use **NLopt** for non-linear optimization.

## 5. Licence
The source code is released under [GPLv3](http://www.gnu.org/licenses/) license.


## 6. Disclaimer
This is research code, it is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of merchantability or fitness for a particular purpose.