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A lightweight differential flatness-based trajectory planner for car-like robots

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Dftpav

A lightweight Spatial-Temporal trajectory planner for car-like robots。

0. Overview

Related Paper:

Please cite the paper below if this repo helps you.

1. Setup

All the tests are conducted in the Linux environment on a computer equipped with an Intel Core i7-10700 CPU and a GeForce RTX 2060 GPU.

Moreover, Our software is developed and tested in Ubuntu 18.04, 20.04 with ROS installed.

ROS can be installed here: ROS Installation.

2. Build on ROS

  1. Install the dependence.

    sudo apt-get install libgoogle-glog-dev libdw-dev libopenblas-dev gfortran
    

    We use Protocol Buffers for parameter configuration. For the installation guide, please refer to this link.

  2. Create an empty new workspace and clone this repository to your workspace:

    cd ~/your_catkin_ws/src
    git clone https://github.com/ZJU-FAST-Lab/Dftpav
    cd ..
    
  3. Compile it.

    catkin_make -DCMAKE_BUILD_TYPE=Release
    

3. Run

Open a new terminal window, cd to ~/your_catkin_ws/ and type:

source devel/setup.bash

Then, run the script:

./run.sh 

Then, you can use the 2D Nav Goal in RVIZ to trigger the planning.

Here is an example:

4. Licence

The source code is released under GPLv3 license.

5. Maintaince

For any technical issue, please contact Zhichao HAN (zhichaohan@zju.edu.cn).

For commercial inquiries, please contact Fei GAO (fgaoaa@zju.edu.cn).

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A lightweight differential flatness-based trajectory planner for car-like robots

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