The Karl Popper Doktorats- und Wissenschaftskolleg (KPK)
The Karl Popper Doktorats- und Wissenschaftskolleg (KPK) advances collaborative research and education in the field of Networked Autonomous Aerial Vehicles (NAV) and makes Klagenfurt a hub in this emerging and disruptive technology. Groups from robotics, pervasive computing, mobile communications systems, multimedia systems, and other disciplines join forces to create an inspiring environment in which faculty members, PhD students, international research fellows, and world-leading labs and companies closely collaborate.
Active knowledge and innovation exchange opens novel perspectives and ensures the best preparation for students aiming at an R&D career in this exciting field. The structure of the program encompasses a cutting-edge research portfolio aiming for scientic excellence linked to a well-chosen and team-oriented education program. All participants are committed to common scientific goals by focusing on a realistic application scenario in autonomous 3D reconstruction with small-scale collaborative aerial vehicles. The international network is a key strength of the program, where 18 highly renowned experts and several outstanding research institutions and companies participate. Members of the doctoral school can therefore easily connect with the worldwide community, generate research at global scale, and obtain feedback from distinguished collaborators. The integrated quality control processes ensure continuous improvement.
The program signicantly strengthens the university’s recently defined area of excellence Networked and Autonomous Systems and also fits well into the multi-disciplinary research cluster Self-Organizing Systems. It bundles and leverages the research activities of the involved AAU groups and establishes in combination with several researchers funded by other sources, including FFG and highly-competitive Horizon 2020 projects a doctoral school of at least 12 students.
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Modular Sensor Fusion
The objective of this PhD thesis is to enable visual-inertial focused modular multi-sensor fusion for robust navigation of computationally constrained aerial vehicles. The multi-sensor fusion system will self-calibrate extrinsics of the newly added sensors, disable/ignore faulty sensors, and automatically compensate for different sensor rates and signal delays. The framework will be optimized to run in real-time on computationally constrained platforms.
Decentralized Mission Planning
The objective of this PhD thesis is to develop and evaluate decentralized algorithms for coordinating a team of mobile aerial robots in order to achieve collaborative 3D reconstruction. The research focuses on how to plan the movement of the individual UAVs such that the 3D reconstruction can be achieved at the specified quality while considering the various constraints of the multi-UAV system. Mission planning should be executed on each UAV by exploiting its local information and data received from the other UAVs.
Optimized Data Transmission
The objective of this PhD thesis is to research and develop the techniques and tools for facilitating the communication/data exchange among the multiple aerial vehicles in the swarm. The use case at hand, distributed autonomous 3D reconstruction, and the tasks of autonomous navigation and coordination and mission planning have to be optimally supported, with respect to the required quality of service (QoS) parameters and respecting the constraints of the aerial network.
Decentralized Time Synchronization
The objective of this PhD thesis is to develop and experimentally assess a decentralized protocol for temporal synchronization of mobile aerial robot networks that fulfills the requirements of sensing for 3D reconstruction in terms of synchronization precision and delay. The protocol should be independent of the used robot platform and communication technology. There will be close collaboration with all other PhD students funded by the KPK in specifying the synchronization requirements and in the experimental performance assessment in the air.