drone_simple_nav

About

This is a minimum implementation of drone navigation.

How it works:

1. One ROS node reads a local point cloud file and streams the point cloud through a ROS topic of type sensor_msgs/PointCloud2. Collision check is performed using the point cloud.
2. The planner uses A* to generate a collision-free path. Then a simple trajectory of constant speed is generated from the path.
3. Real-time position and velocity commands are derived from the trajectory and used for visualization. The commands follow the data structure defined in mavros_msgs/PositionTarget.

Installation

Before installing this project, please make sure the following dependencies have been successfully installed and configured.

ROS1: https://wiki.ros.org/noetic/Installation/Ubuntu

sudo apt install ros-noetic-octomap*
sudo apt install ros-noetic-octovis
sudo apt install graphviz graphviz-dev
pip install octomap-python
pip install pyquaternion
pip install scipy
pip install transitions[diagrams]

Then, install this project as a ROS workspace

git clone https://github.com/Amos-Chen98/drone_simple_nav.git
cd drone_simple_nav
catkin build
echo "source $PWD/devel/setup.bash" >> ~/.bashrc

Usage

Trajectory planning

roslaunch simulator run_sim.launch

RViz will pop up, then you can set the global target using 2D Nav Goal. The drone will perform 3D planning and fly to the target.

Currently, the z position of the target is set in src/simulator/launch/run_sim.launch.

There are three available navigation modes, controlled by the argument replan_mode in src/simulator/launch/run_sim.launch.

1. global: Plans once, generating a complete trajectory from the start to the target position.
2. fix_time: (Default) Continuously performs local planning until reaching the target, with a fixed replanning interval.
3. rush: Continuously performs local planning until reaching the target, immediately triggering replanning after the last replanning is finished.

Other major configurable parameters exist in the following three files:

src/simulator/launch/run_sim.launch

src/planner/launch/planner_config.yaml

src/planner/launch/manager_config.yaml

Customized development

1. Batch random generation of Gazebo world

Run src/simulator/scripts/generate_worlds.py

This command will automatically generate a batch of gazebo world files.

The configurable parameters are listed in src/simulator/scripts/generator_config.yaml

2. Generate octomap and pointcloud offline from Gazebo world

Below are the instructions on how to generate ground truth octomap and/or pointcloud.

This function is based on the package sim_gazebo_plugins. To use the plugin, you need to edit your desired .world file to recognize the plugin. Simply open your .world file in a text editor and add the following line just before the final <world> tag (i. e. in between the <world> tags):

(If you are using the default poles.world, or any worlds generated from generate_worlds.py, this step is not required because the plugin has already been included.)

<plugin name='gazebo_octomap' filename='libBuildOctomapPlugin.so'/>

To generate a .pcd file and a .bt file , execute the following commands:

roslaunch simulator load_world.launch gazebo_world:=<your_world_file>
# Replace <your_world_file> with the filename of the world you wish to build a map from. This name should not not contain ".world"

rosservice call /world/build_octomap '{bounding_box_origin: {x: 0, y: 0, z: 15}, bounding_box_lengths: {x: 30, y: 30, z: 30}, leaf_size: 0.1, filename: output_filename.bt}'

Then the .pcd file and the .bt file will be generated in your current path.

The rosservice call includes adjustable variables: the bounding box origin and lengths, both in meters.

The lengths extend symmetrically in both (+/-) directions from the origin. For example, with an origin at (0, 0, 0) and bounding_box_lengths {x: 30, y: 30, z: 30}, the bounding box spans -15 to +15 meters in the X and Y directions, and 0 to 30 meters in the Z direction.