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EGO Planner V2.1

This branch builds upon the main_ws branch, providing the following new features.

Dec 23, 2023 update:

  • Support for terrestrial drones
  • Angular Motion (non-holonomic) constraint
  • Heterogeneous swarm coordination
  • Habitat simulator integration
  • Path guided local target selection

Please refer to documents for detailed description of new features and code modifications.

The main_ws branch represents a streamlined version of the main_ws in EGO Planner V2, focusing on enhancing code organization and compilation without introducing major modifications.

Environment Setup

To set up the environment, follow the steps below. We recommend using a virtual environment. You can also use the system-installed ROS and install habitat-sim using source or pip associated with the ROS Python interpreter, which is not easy.

# System dependencies (Ubuntu)
sudo apt install libgl1* 

# Create and activate a virtual environment
mamba create -n ego python=3.9 -y
mamba activate ego

# Install ROS related stuff
mamba install ros-noetic-desktop-full ros-noetic-joy -c robostack-staging -y
mamba install compilers cmake=3.12 pkg-config make ninja colcon-common-extensions catkin_tools -y

# Other handy tools
mamba install habitat-sim=0.2.4 -c aihabitat -y
mamba install armadillo casadi=3.6.3 ompl=1.5.2 -y

# Install Open3D
pip install open3d==0.17.0

# Install acados
cd $CONDA_PREFIX
git clone https://github.com/acados/acados.git
cd acados
git checkout v0.2.6
git submodule update --init --recursive
mkdir build
cd build
cmake -DACADOS_WITH_QPOASES=ON -DACADOS_WITH_OSQP=ON -DACADOS_INSTALL_DIR=$CONDA_PREFIX ..
make install -j 16
cd ..
pip install interfaces/acados_template

Now change working directory to src/ego_planner/scripts to generate acados code for diffdrive MPC.

mamba activate ego
python diffdrive_acados.py

Go back to the top repo directory and build the workspace.

mamba activate ego
catkin_make # or catkin build

Running Demos

# Activate the virtual environment and source the setup file
mamba activate ego
source devel/setup.bash

# Run launch files in the node_launcher package (e.g. single_diffdrive_interactive_habitat.launch)
roslaunch node_launcher single_diffdrive_interactive_habitat.launch

Known & Potential Issues

  1. The SelectedPointsPublisher RViz plugin does not work well within the virtual environment.

  2. Node moving_obstacles and ego_planner/launch/obstacle_run.launch are not tested due to lack of joy stick. ego_planner/launch/drone_detect.launch is also not tested.

  3. Aerial agents will only avoid other terrestrial agents horizontally. No flying-over behaviour.

  4. Optimizer can fail if free space is blocked by a close-up and slowly-moving agent, when operating in narrow passages. Set identical maximum velocity to relieve this problem.

  5. 3D dynamic A* implemented in this repo tends to slow down the entire navigation process and result in crashes. Set reasonable goals when using an aerial robot.

  6. Failed planning at the end of the current trajectory may occasionally cause crashes.

Bibliography

The original repo EGO-Planner-v2: https://github.com/ZJU-FAST-Lab/EGO-Planner-v2.

The original paper can be cited as:

@article{
    doi:10.1126/scirobotics.abm5954,
    author = {
        Xin Zhou,
        Xiangyong Wen,
        Zhepei Wang,
        Yuman Gao,
        Haojia Li,
        Qianhao Wang,
        Tiankai Yang,
        Haojian Lu,
        Yanjun Cao,
        Chao Xu,
        Fei Gao
    },
    title = {Swarm of micro flying robots in the wild},
    journal = {Science Robotics},
    volume = {7},
    number = {66},
    pages = {eabm5954},
    year = {2022},
    doi = {10.1126/scirobotics.abm5954}
}