Control of a hovering AUV simulated using HoloOcean. This implements the full robotics stack include various algorithms for state estimation, low-level control, and planning. HoloOcean is simple to use, and the HoveringAUV is easy to control, making this a perfect platform for experimenting and testing of various robotics algorithms.
The code is organized into the python module auv_control. This consists of 3 submodules -
estimation, control, and planning - along with various other helper functions. The following algorithms have been implemented:
- Base module
- State class - wrapper class to standardize how our state is represented.
- scenario - python dictionary with the example HoloOcean scenario to run.
- Estimation module
InEKF- Implementation of the invariant EKF with the IMU sensor as the process model and GPS, DVL, magnetometer, and pressure sensor as the update step.
- Control Module
LQR- Simple LQR controller using linearized state dynamics and euler angles. (Simple improvement to this would be something using Lie Groups)
- Planning Module
RRT- Loads up various obstacles in the environment, and plans a trajectory from one side of the environment to the other using RRT.Traj- Various predefined trajectories to test controllers on.
To run the simulation, first install all dependencies
pip install -r requirements.txt
Then simply run the script
python run.py -s -p
where -s shows the simulation and -p shows the plotter. By default these are both off. On first run, it will download the HoloOcean binaries which may take a minute. To see a full list of simulation options, run
python run.py -h