lu-tju/grad_traj_optimization

Gradient-Based Online Safe Trajectory Generator

GTOP:Gradient-Based Trajectory Optimizer

(This repo is mainly developed and maintained by Boyu Zhou, please contace him if necessary)

1.Introduction

Gradient-Based Online Safe Trajectory Generation is trajectory optimization framework, for generating a safe, smooth and dynamically feasible trajectory based on the piecewise line segment initial path. The planning problem is formulating as minimizing the penalty of collision cost, smoothness and dynamical feasibility.

Authors:Fei Gao,Boyu Zhou,and Shaojie Shen from the HUKST Aerial Robotics Group.

Disclaimer

This is research code, any fitness for a particular purpose is disclaimed.

Related Paper

• Gradient-Based Online Safe Trajectory Generation for Quadrotor Flight in Complex Environments, Fei Gao, Yi Lin and Shaojie Shen

Video of this paper can be found here.

         

If you use this generator for your academic research, please cite our related paper.

@inproceedings{Fei2017IROS,
	Address = {Vancouver, Canada},
	Author = {F. Gao and W.Wu and Y. Lin and S. Shen},
	Booktitle = {Gradient-Based Online Safe Trajectory Generation
for Quadrotor Flight in Complex Environments},
	Title = {Proc. of the {IEEE/RSJ} Intl. Conf. on Intell. Robots and Syst.},
	Month = Sept.,
	Year = {2017}}
}

2.Prerequisities

Our testing environment: Ubuntu 14.04, ROS Indigo.

We use NLopt as optimization solver. Installation is straight forward. Just download, extract and compile:

mkdir build
cd build
cmake ..
make

Finally you should install it.

sudo make install

Detailed information can be found here.

Note:The default installation prefix of NLopt is /usr/local

3.Build on ROS

Clone the repository to your catkin workspace and catkin_make. For example:

  cd ~/catkin_ws/src
  git clone https://github.com/HKUST-Aerial-Robotics/grad_traj_optimization.git
  cd ../
  catkin_make
  source ~/catkin_ws/devel/setup.bash

4.Random Map and Waypoints Example

Open two terminals and run:

  roslaunch grad_traj_optimization traj_rviz.launch
  roslaunch grad_traj_optimization random.launch

After running and open rviz with traj.rviz file, you should find a randomly built collision map with some waypoints going through it. Then a smooth and collision free trajectory is generated.

5.Random Map and Clicked Waypoints Example

Similarly, run:

  roslaunch grad_traj_optimization traj_rviz.launch
  roslaunch grad_traj_optimization click.launch

Likewise, a random collision map is built but with fewer obstacles. Then you can click in rviz using 2D Nav Goal to add some waypoints. The Z coordinate of each waypoint is set to 2.0. The default waypoint number is 7 and you can change it in click.launch. Trajectory is generated as long as enough waypoints are added.

Note:Trajectory with too many segments or with sharp corner is difficult to optimized and is tend to fail.

6.Text Input Example

If you want to set the collision map and waypoints as much as you like, run

  roslaunch grad_traj_optimization traj_rviz.launch
  roslaunch grad_traj_optimization text_input.launch

Instead of randomly generated ,the collision map and waypoints in this example is specified in text_input.launch.Just change it to what you want.

7.Acknowledgements

We use NLopt for non-linear optimization and sdf_tools for building signed distance field.

8.Licence

The source code is released under GPLv3 license.