Working Student (f/m/x) - LiDAR Sensors Integration on a Drone Swarm

What to expect:

In search and rescue scenarios, dense vegetation and environmental occlusions can significantly limit the effectiveness of aerial search operations. Visibility-aware navigation can improve how drone teams collect information by guiding them towards viewpoints that maximize useful observations while minimizing redundant coverage. Combining LiDAR sensing, computer vision, and autonomous UAV systems enables the creation of visibility maps that can support coordinated navigation and decision-making for multiple drones. The objective of this project is to investigate how visibility information can be generated and used to guide drone swarms in complex environments.

Your tasks:

• Investigate and implement computer vision techniques for creating visibility maps from LiDAR and sensor data
• Develop and evaluate methods for visibility-aware guidance of multiple UAVs
• Design and conduct experiments in simulation and real-world environments
• Support field campaigns using UAV hardware platforms and LiDAR sensors
• Analyze experimental data and assess system performance

Your profile:

• Currently enrolled in a Master's program in Robotics, Geomatics, Remote Sensing, Computer Science, or a related field
• Programming experience in Python and/or C++
• Interest in computer vision, robotics, UAVs, and autonomous systems
• Experience with ROS, LiDAR, or simulation environments is beneficial