Autonomous Aerial Robotics

This is a collection of projects for the course ELEC5660 (Introduction to Aerial Robotics) @ HKUST, 2025 Spring. Instructor: Prof. Shaojie SHEN.

Detailed code implementation can be found in the Github code repo.

Project Overview

Developed control algorithms, trajectory planning, and sensor fusion techniques for an autonomous aerial robot by utilizing rigid-body dynamics, A* path planning, PnP-based localization, visual odometry, and (augmented state) Extended Kalman Filter (EKF)-based state estimation to enable vision-based indoor navigation and real-time flight control.

The whole course’s projects are divided into the following sub-projects.

Sub-projects

• Project 1 - Phase 1: Controller Design and Simulation
  • Keywords: PID, Quadrotor Dynamics
• Project 1 - Phase 2: Trajectory Planning and Generation
  • Keywords: Trajectory Planning, Optimization-based Trajectory Generation, Minimum Snap Trajectory, (un)constrained Quadratic Programming
• Project 1 - Phase 3: Path Planning and Obstacle Avoidance
  • Keywords: Path Planning, Obstacle Avoidance, A*, Dijkstra’s Algorithm
• Project 1 - Phase 4: Autonomous Control of Real Drone
  • Keywords: Autonomous Control, Motion Capture System
• Project 2 - Phase 1: 3D-2D Pose Estimation (PnP)
  • Keywords: 3D-2D Pose Estimation, PnP, OpenCV, SVD, Linear Estimation
• Project 2 - Phase 2: Stereo Visual Odometry
  • Keywords: Stereo Visual Odometry, PnP, Optical Flow, RANSAC, OpenCV
• Project 3 - Phase 1: EKF
  • Keywords: Extended Kalman Filter (EKF), IMU, PnP, Sensor Fusion, State Estimation
• Project3 - Phase 2: Augmented State EKF
  • Keywords: Augmented State EKF, IMU, PnP, Stereo VO, Sensor Fusion, State Estimation