Internship/m.sc. Thesis: Sensor Fusion and Semantic Projection for Power Line Inspection

12 set - Bolzano
Fraunhofer Italia

The topic:
- Sensor Fusion and Semantic Projection for Power Line Inspection_

This internship and thesis topic focuses on the development of a sensor fusion and semantic projection framework for UAV-based inspection of medium-voltage power lines. The objective is to integrate high-resolution RGB imagery and LiDAR data to produce semantically enriched and colorized 3D representations of power line components. The approach combines the semantic understanding of deep neural networks (DNNs) with the geometric precision of LiDAR sensing to enable accurate and interpretable inspection data.

RGB images will be processed using DNN-based object detection and segmentation models to identify components such as insulators, cross-arms, clamps, and vegetation intrusions. These detections will be projected into LiDAR point clouds using precise extrinsic calibration and temporal synchronization between the sensors. The resulting 3D reconstructions will be geometrically accurate, semantically annotated, and visually enhanced with RGB color information.





A further focus will be on data prioritization and reduction for efficient communication between UAV and ground station. Only relevant or annotated areas, such as those containing critical structures or defects, will be transmitted or stored.

Requirements:
- You are a university or high school student in a MINT discipline and looking for hands-on experience.
- You have knowledge of programming in C++ or Python and a basic understanding of cameras and LiDAR sensors.
- You work independently, systematically, and with a high level of commitment, creativity, and team spirit.
- You are an EU citizen or have a valid work permit for Italy.
- You are proficient in English; knowledge of Italian or German is an advantage.
- The internship is carried out in presence at our premises in Bolzano.

Your task:
Your main activity will be to implement and validate sensor fusion and semantic mapping concepts using UAV data. You will develop algorith

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