EVA-planner

EVA-planner: an EnVironmental Adaptive Gradient-based Local Planner for Quadrotors.

0. Overview

Author: Lun Quan, Zhiwei Zhang, Xingguang Zhong, Chao Xu and Fei Gao from ZJU FAST Lab.

Video Links: Google, Bilibili(for Mainland China)

All planning algorithms along with other key modules, such as mapping, are implemented in adaptive_planner
- path_searching: includes multi-layer planner (A*, low-MPC and high-MPCC).
- path_env: includes online mapping algorithms for the planning system (grid map and ESDF(Euclidean signed distance filed)).
- path_manage: High-level modules that schedule and call the mapping and planning algorithms. Interfaces for launching the whole system, as well as the configuration files are contained here

Requirements: ubuntu 16.04, 18.04 or 20.04 with ros-desktop-full installation

Step 1. Install Armadillo, which is required by uav_simulator.

sudo apt-get install libarmadillo-dev

Step 2. Clone the code from github.

git clone https://github.com/ZJU-FAST-Lab/EVA-planner.git

Step 3. Compile.

cd EVA-planner
catkin_make

source devel/setup.bash
roslaunch plan_manage simulation.launch

Then you can enter G with the keyboard and use the mouse to select a target.

The framework of this repository is based on Fast-Planner by Zhou Boyu who achieves impressive proformance on quaorotor local planning.
We use NLopt for non-linear optimization.
The hardware architecture is based on an open source implemation from Teach-Repeat-Replan.
The benchmark compared in our paper is ICRA2020_RG_SDDM.

The source code is released under GPLv3 license.

For any technical issues, please contact Lun Quan (lunquan@zju.edu.cn) or Fei GAO (fgaoaa@zju.edu.cn).

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