Quadrotor Control, Path Planning and Trajectory Optimization

(Click above image for real quadrotor demos)

Following MEAM 620 Advanced Robotics course at University of Pennsylvania.

(For Penn students: DO NOT spoil the fun by looking at this repo and not working on your assignments! and most importantly, DO NOT violate the honor code!)

This repo includes matlab code for:

• Quadrotor PD controller
• Path planning algorithms (Dijkstra, A*)
• Trajectory optimizations (Minimum Snap/Acceleration Trajectory)

Please cite this work using the following bibtex if you use the software in your publications

@software{Lu_yrlu_quadrotor_Quadrotor_Control_2022,
  author = {Lu, Yiren},
  doi = {10.5281/zenodo.6796215},
  month = {7},
  title = {{yrlu/quadrotor: Quadrotor Control, Path Planning and Trajectory Optimization}},
  url = {https://github.com/yrlu/quadrotor},
  version = {1.0.0},
  year = {2017}
}

PD Controller

• Run code: change trajectories in file control/runsim.m and run.
• See quadrotor_dynamics.pdf for dynamic modeling of the quadrotor.
• See control/controller.m for implementation of the PD controller.
• Visualization below. Desired (blue) vs Actual (red)

Trajectory 1: Step

Trajectory 2: Circle

Trajectory 2: Diamond

Path Planning and Trajectory Optimization

• Run code: traj_planning/runsim.m and run path 1 or path 3.
• See project_report.pdf for more details about trajectory generation
• See traj_planning/path_planning/dijkstra.m for implementation of path finding algorithms (dijstra, A*).
• See traj_planning/traj_opt7.m for implementations of minimium snap trajectory.
• See traj_planning/traj_opt5.m for implementations of minimium acceleration trajectory.
• Visualization below.

Minimum Acceleration Trajectory

Minimum Snap Trajectory

(with way points constraints)