Autonomous multi-UAV for the characterization of remote and isolated targets
The project AutoTarget aims to develop an autonomous, task-distributed drone network to improve the characterization of isolated, remote targets in a time and resource efficient manner. The project will be carried out in close collaboration between the Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology (HZDR-HIF), the Karlsruhe Institute of Technology, Institute of Industrial Information Technology (KIT-IIIT), and the Center for Advanced System Understanding (CASUS). The key challenges of the project include the development of drone and multi-sensor technology, real-time processing and automation.
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HZDR-HIF contributes a strong background in drone design, drone-borne data acquisition, spectral imaging, multi-sensor systems as well as data processing and machine learning. HZDR-HIF further provides most of the equipment and facilities required, such as the drone platforms, different spectral or geophysical sensors and computing facilities for algorithm development. The KIT-IIIT contributes the missing in-depth knowledge on sensor technology, information fusion and modeling for navigation, communication and automated decision-making for autonomous vehicles. CASUS will complement the competences in machine learning and real-time anomaly detection and cover the project expenses of approx. 491 kEuro. The budget covers two PostDocpositions for the project duration of 3 years, as well as costs for publication, travel and technical parts. One PostDoc will be hosted at CASUS, the other will be shared between HZDR-HIF and KIT-IIIT, with frequent visits at CASUS.
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With the highly interdisciplinary approach including image processing and machine learning, parallelization, automation and interconnectivity to reduce the time and resource consuming processing of high-dimensional data by prior, automated selection, the project aligns well with the vision of all three partners. With their complementing scientific backgrounds, the partners will benefit strongly and long-term from the knowledge transfer. The establishment of a joint project, connected with annual workshops, will hopefully strengthen the collaboration between both institutes and pave the way for future projects.
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