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Autonomous VIO-based Quadrotor

This project is the simulation of Stereo Visual Inertial Odometry (VIO) on a quadrotor modeled from CrazyFlie 2.0. In the simulation, the quadrotor is set up with an on-board IMU and a stereo camera rig.

Pipeline

  • A* algorithm for shortest path searching and minimum snap for trajectory smoothing.
  • Geometric Nonlinear Controller for trajectory tracking.
  • RANSAC for robust feature matching given stereo correspondences to recover camera pose.
  • Error State Kalman Filter to acquire accurate quadrotor pose estimation.

Run

  • Setup the environment:
  pip install .
  • Run VIO simulation:
  python sandbox.py
  • New maps can be customized through JSON file and saved under proj/util/.

Examples

  • Shortest path generated by A* algorithm, pruned waypoints and smoothed trajectory:

  • Trajectoy tracking: