This PhD project focuses on developing robust and adaptive communication and computing frameworks for multi-UAV operations in Innovative Air Mobility (IAM) scenarios. The goal is to enable autonomous UAVs to perform mission-critical tasks even under adverse conditions, including GNSS unavailability, signal jamming, or degraded radio environments.
The central aim of the thesis is to extend communication concepts from single UAVs to coordinated multi-UAV systems. By deploying multiple UAVs that are centrally supervised and dispatched, swarm-like mechanisms can be exploited to efficiently handle mission-specific, spatially and temporally clustered data. This approach improves data transfer efficiency and supports innovative navigation concepts, including enhanced map quality and reduced map-building time. Both single- and multi-agent SLAM require a careful split of computation between local (onboard) and remote (edge or cloud) instances, which in turn imposes new requirements on communication. The research will therefore develop novel communication solutions in the context of emerging 6G standards and wireless mesh networks.
The project combines resilient ad-hoc networking, edge-assisted computation, and cooperative simultaneous localization and mapping (C-SLAM) to support dense, multi-agent UAV operations. Visual and map data are efficiently compressed, fused, and synchronized to sustain robust operation in dynamic urban or disaster-management scenarios. By integrating autonomous UAVs as active agents within a distributed digital twin, the project links communication resilience directly to navigation performance, safety, and mission-critical decision-making.
Objectives:
- extend communication frameworks from single UAVs to coordinated multi-UAV systems, exploiting swarm-like mechanisms to efficiently handle spatially and temporally clustered mission-specific data
- develop resilient multi-link networking solutions based on emerging 6G standards and wireless mesh architectures to ensure robust connectivity under interference, jamming, or degraded GNSS conditions
- design adaptive cooperative SLAM frameworks for multi-agent UAV operations, supporting reliable localization, mapping, and trajectory planning in complex environments
- implement efficient compression, fusion, and synchronization of visual and map data to enable real-time operation on bandwidth- and computation-constrained platforms
- optimize the distribution of computation between onboard, edge, and cloud instances to balance latency, reliability, and processing load in single- and multi-agent scenarios
- validate communication and navigation frameworks in realistic urban and disaster-management scenarios, demonstrating integration of UAVs and UGVs within a distributed digital twin for situational awareness and mission-critical decision-making
Tasks:
- independent and cooperative qualification through scientific research within one of the PhD study projects on offer
- training in the technical tasks of the individual dissertation topics through study of the literature and in making the objectives more precise
- working on the individual PhD study project with experimental, numerical in collaboration with other RTG members (fellow students and supervising professors)
- implementation of the planned research program, evaluation and interpretation of the results and transferring them to a RTG internal ex-change platform, elaboration and presentation of the state-of-the-art in the respective research fields
- participation in lectures, workshops and summer schools according to the guidelines of the RTG curriculum
- supporting scientific graduation work (Bachelor/Master/Diploma) in the subject-specific research field
- regular reporting on research progress to the supervising professors
- publishing the results of the research work individually and in concert with others
- cooperative maintenance of exchange platforms (database, information pages, etc.)
- summarizing the results of the individual PhD study project in a dissertation within the due time of three years
- Successful candidates will work together with an experienced PhD researcher at the Institute of Photogrammetry and Remote Sensing and together with other chairs being part of the RTG.
Table of Content
Summary
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Benefits
- Pioneering Research Environment: Shape the future of advanced air mobility through involvement in innovative drone-related projects that bridge technology, urban planning, material sciences, sensors and aviation. With the upcoming Smart Mobility Lab in Lusatia, Saxony, you will have access to state-of-the-art and extensive facilities for experiments. This includes a hall measuring 100x100x30 meters and outdoor space (available from 2027).
- Cross-Disciplinary Collaboration: Immerse yourself in a highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as engineering, data science, urban studies, and aerospace.
- Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in drone technology, data analytics, regulatory aspects, project management, and leadership skills. This ensures you graduate not only as a specialist in your field but also as a well-rounded professional.
- Global Networking: Collaborate with our network of local and international partners, fostering connections that transcend geographical boundaries and enrich your academic and professional network. This includes a paid research stay abroad for three months.
- Career Advancement: Receive dedicated support for fellowship applications and tailored guidance for your career.
- Quality of Life in Dresden: Experience a high quality of life in Dresden, with its dynamic urban scene, relatively affordable living, rich cultural offerings, and vibrant nightlife.
Requirements
- Good or very good university degree in electrical engineering, computer science, computer engineering or comparable
- Solid background in wireless communication, networked systems, or distributed computing
- Knowledge of autonomous systems, multi-robot coordination, SLAM techniques and experience in software development and simulation environments (e.g., Python, C++, ROS, MATLAB)
- TU Dresden are looking for first-class graduates with expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute determination to submit the dissertation after three years of research.
Check also:
2026 Fully Funded Humboldt Research Fellowship
2026 Konrad Adenauer Foundation Scholarship
Application Deadline
February 4, 2026How To Apply
- Please submit your detailed application including a cover letter detailing your research interests stating the job-ID "RTG 2947-T9/2" along with your curriculum vitae, academic transcripts with marks, a letter of recommendation and your publications (if applicable) by February 4, 2026 (stamped arrival date of the university central mail service or the time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to [email protected] or to:
Further questions regarding this call can be addressed to Prof. Dr. Frank Fitzek ([email protected]).
For more information, kindly visit TU Dresden webpage.
