ELEC5660 is an HKUST PG course which gives a comprehensive introduction to aerial robots. The goal of this course is to expose students to relevant mathematical foundations and algorithms and train them to develop real-time software modules for aerial robotic systems. Topics to be covered include rigid-body dynamics, system modeling, control, trajectory planning, sensor fusion, and vision-based state estimation. Students will complete a series of projects that combine into an aerial robot that is capable of vision-based autonomous indoor navigation.
Instructor: Shaojie SHEN
TAs: Yang Xu (yxuew@connect.ust.hk), Pusen Gao (pgaoak@connect.ust.hk)
Lab: HKUST Aerial Robotics Group
- course_node: notes
- assignments: assignment code
- lab: lab notes
- workspace_template: Terraform template for setting up cloud workspace
| Name | Description | Demo |
|---|---|---|
| proj1phase1 | Implement a basic controller for quadrotor trajectory tracking |  |
| proj1phase2 | Implement trajectory generation with minimum jerk/snap optimization |  |
| proj1phase3 | Implement A* path planning and intergrate with trajectory generation and control |  |
| lab1 | Assemble and fly a drone in manual mode and prepare hardware & software environment for later labs |  |
| proj1phase4_lab2 | Fly the drone in autonomous control mode with OptiTrack motion capture system and analyze flight data |  |
| proj2phase1 | Implement Perspective-n-Point (PnP) algorithm for vision-based state estimation |  |
| proj2phase2 | Implement stereo visual odometry for 6-DOF pose estimation |  |
| proj3phase1 | Implement an Extended Kalman Filter (EKF) for sensor fusion of IMU and visual odometry |  |
| proj3phase2 | Implement an augmented EKF for sensor fusion of IMU, visual odometry, and tag-based pose estimation |  |
| proj3phase3_lab3 | Integrate the whole system onboard for tracking trajectory or autonomous flight without OptTrack motion capture system |  |
In order to facilitate development and testing of algorithms, we provide a simulator based on NVIDIA Isaac Sim. The simulator supports realistic physics simulation, sensor simulation (IMU, stereo camera), and ROS interface for easy integration with your code. You can find the simulator code and instructions in the lab/simulator directory.
For questions and suggestions, please contact TAs