This project aims to develop an autonomous UAV system for mapping, inspection, and progress monitoring in complex underground construction environments.
Our focus is on integrating autonomous flight, multi-modal perception, semantic mapping, BIM-guided planning, and 3D reconstruction into a real-world drone system.
Students may work on topics including:
- LiDAR-, camera-, and depth-sensor integration
- SLAM and localization in GPS-denied environments
- Autonomous 3D coverage and inspection planning
- BIM-guided trajectory and viewpoint planning
- Open-vocabulary semantic segmentation and semantic mapping
- Strong programming, communication, collaboration, organization, and planning
- Proactive and fast self-learner
- Interest in robotics, autonomous systems, computer vision, 3D perception, or aerial robotics
- Familiarity with software: ROS2, Python, C++, Linux, Bash, Git, docker
- Familiarity with semantic segmentation or foundation / open-vocabulary vision models
- Experience with drone or mobile-robot autonomy
- Experience with trajectory planning or coverage planning
- Understand the complete autonomy stack of a real UAV system
- Work with synchronized LiDAR, RGB, depth, and onboard-computing systems
- Develop and evaluate SLAM and mapping algorithms for GPS-denied environments
- Design autonomous 3D inspection and coverage-planning algorithms
- Working with senior students and faculty advisors
Not a hard limit. We care more about talent and potential.