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