A minimal PyBullet simulation of a two-wheeled self-balancing robot. Two threads run:

• sim_thread:

  1. Reads IMU orientation and gyro-rate from PyBullet
  2. Adds small noise to pitch
  3. Filters via Kalman1D and sends error to PID
  4. Commands wheel velocities to balance

• plot_thread:

  1. Collects (time, raw_pitch, filtered_pitch, raw_rate, filtered_rate, control)
  2. Updates four live Matplotlib subplots (pitch, rate, PID output, ESS)

1. Clone repo

   git clone <repo-url>
   cd <repo-folder>

2. Install dependencies

   ./install.sh

3. Run simulation

   python main.py

   • A PyBullet GUI window launches with three PID sliders (P_gain, I_gain, D_gain).
   • Adjust sliders to tune balance.
   • A separate Matplotlib window shows live data plots.

.
├── controllers.py      # PID class
├── filters.py          # Kalman1D class
├── simulation.py       # setup_pybullet()
├── main.py             # sim_thread + plot_thread
├── balance_bot.urdf    # Robot URDF
├── requirements.txt    # Dependencies list
├── install.sh          # “pip install -r requirements.txt”
└── README.md           # (this file)

• For detailed Kalman/PID code, see filters.py and controllers.py.