Master Thesis AI based Drone Navigation in Complex Environments

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Company Description

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Bosch R&D Center Lund stands for modern development in cutting edge technology in the areas of connectivity, security, mobility solutions and AI. We are growing rapidly and looking for people to join us on our mission to become the Bosch Group's 1st address for secure connected mobility solutions. We are working on a range of interesting projects, with a particular focus on software development for the automotive industry, electrical bicycles and Internet of Things.

Job Description

Problem statement

In this Master Thesis in Software Engineering,we will focus on developing a Proof of Concept, for an AI-driven navigation system for autonomous drone flight at low altitude. One of the major challenges in this domain is achieving safe and reliable navigation under constraints such asunreliable or absent GPS signals, dynamic obstacles, limited onboard computational resources, and restricted visibility.

To operate effectively in such environments,we must rely on onboard sensorssuch as cameras, IMU, and LiDAR, and combine them throughsensor fusion,computer vision, andintelligent motion planning. In addition,satellite map datacan be integrated as a complementary prior to increasing environmental awareness and provide geographic context when GPS information is weak or missing.

Furthermore,traditional rule-based navigation algorithms often fail under these conditions, making it necessary to explore a newAI-driven approachthat can adapt in real time while ensuring safety, energy efficiency, and robustness during low-altitude operations.

Proposed solution

The proposed solution is to develop an AI-driven navigation system as a Proof of Concept (POC), that enables a drone to operate safely at low altitude even when GPS signals are unreliable or absent.

The system will combine:

• Deep learning-based motion planning, allowing the drone to adapt its trajectory in real time
• Computer vision methods for detecting obstacles and understanding the surrounding environment
• Sensor fusion integrating data from IMU, camera, satellite map data and optionally LiDAR to maintain accurate localization without GPS
• Simulation based validation, where all algorithms will be trained and tested in environments such as AirSim, PX4 or Gazebo before any real-world deployment

Qualifications

• An student in Information Technology, Computer Science, Electronics, Mathematics or Physics.
• Have relevant coursework or knowledge in data science, control systems, and AI.
• Experienced with or have at least basic programming knowledge in Python, C++ or similar languages.
• Self-driven, able to take initiative and move the project forward independently.

A person with team spirit, social skills, and genuine curiosity for robotics, AI and autonomous systems.

Additional Information

Supervisors: Ibrahim Yilmaz

We encourage to have a team of 2 master thesis students working on the thesis.

Please note:Only applications from students located in the area of Lund are accepted.

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