Mr. Aleksej Buller Profile

Aleksej Buller

at Fraunhofer IOSB

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Author

Publications (5)

Proceedings Article | 13 November 2024 Presentation + Paper

Project HUGIN: heterogeneous unmanned group of intelligent USVs

Wilmuth Müller, Florian Segor, Joanna Müller, Cosmin Delea, Aleksej Buller, Dirk Mühlenberg, Nico Zantopp, Johannes Oeffner

Proceedings Volume 13207, 1320703 (2024) https://doi.org/10.1117/12.3031679

KEYWORDS: Sensors, Inspection, Autonomous vehicles, Artificial intelligence, Video, Human-machine interfaces, Surveillance, Control systems, Unmanned vehicles, Object detection

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Due to the current global political situation, threats to critical maritime infrastructures such as LNG terminals, ports, offshore wind farms, subsea pipelines and cables tend to increase. The protection of infrastructures is essential to prevent deterioration of societal structures and to maintain essential services and functions that impact the well-being and livelihood of citizens. To counter this threat, permanent protection is necessary, which is difficult to achieve through surveillance technology operated by people for reasons of cost and personnel. One solution is to deploy a cooperating team (swarm) of unmanned surface vehicles (USVs) that coordinate with each other and independently carry out security tasks such as patrolling or surveillance and react intelligently to suspicious events.

Within the Fraunhofer project HUGIN “Heterogeneous Unmanned Group of INtelligent surface vehicles” the use of heterogeneous autonomous USVs for monitoring critical infrastructure and inspecting ship hulls was developed and tested. Up to three vehicles (two different platform types and heterogeneous sensor technology) were used. The team was assigned a joint task, which had to be divided into subtasks.

The subtasks were forwarded to the vehicles with the appropriate capabilities to be completed independently. The autonomous mission processing and coordination of the three USVs was investigated. The algorithms were tested in dynamic cooperative operation with parallel execution of specific subtasks. To enable the efficient, effective and flexible operation of such systems and the integration of the operator into the overall system, we used the Management by Objective (MbO) concept. MbO for parallel operating autonomous USVs is separated into three main aspects: Vehicle autonomy, Product creation control cycle, and Mission management.

Both, the autonomous cooperative behavior of the vehicles which affect vehicle autonomy as well as mission management and the operator-independent sensor data evaluation (product generation) were further developed and tested in HUGIN.

Proceedings Article | 13 November 2024 Presentation + Paper

Autonomous sensor control for mobile platforms operating in teams

I. Tchouchenkov, F. Segor, M. Kollmann, A. Buller

Proceedings Volume 13207, 1320709 (2024) https://doi.org/10.1117/12.3031541

KEYWORDS: Sensors, Reconnaissance, Cameras, Control systems, Autonomous vehicles, Evolutionary algorithms, Surveillance, Safety, Reconnaissance systems

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New algorithms for appropriate planning and dynamic control of pan-tilt-zoom sensors (stationary or mounted on mobile systems) in in context of reconnaissance missions have been developed at Fraunhofer IOSB. These algorithms are based on the prior proposed solutions for an efficient control of robotic vehicles and groups of heterogeneous robotic vehicles.

In this paper two specific algorithms (deterministic and non-deterministic) are referenced, and it is exploited how these algorithms - originally developed for the control of unmanned vehicles of potential different domains – can be adapted to also support the intelligent autonomous sensor control. The aim is to maximize the effectiveness of these sensors when used in reconnaissance missions.

The deterministic algorithm is based on extensive pre-planning that considers all relevant aspects of the task at hand and the optical sensors to be used like target area, restricted zones, fields of view, resolutions, zoom, and uses approximations and assumptions to determine the best possible area coverage. The non-deterministic algorithm does not undertake preplanning but rather provides basic behaviors and mission relevant compiled information that is used by the autonomous control system to identify the most reasonable actions based on the current situation.

Both algorithm types are suitable for the autonomous control of (heterogeneous) cooperative sensors without any operator interaction. To provide effective and efficient reconnaissance, the usage of each sensor assigned to the operation must be optimized and depending on the task ensure best possible coverage of the mission-relevant area, focus on certain areas by increasing the scanning cadence, etc. To provide sufficient image resolution and quality, the footprint should cover each specified target for a defined time period with a suitable zoom level. Changing alignment angles and relative positions must be continuously taken into account. Therefore, regarding sensors mounted on mobile systems (flying, swimming or driving) planning and control need to be fast and reliable in order to take the movements of the carrier platform into account. The theoretical foundations and practical approaches of the algorithms are compared and discussed.

Proceedings Article | 17 October 2023 Presentation + Paper

Area reconnaissance with heterogeneous groups of autonomous systems

I. Tchouchenkov, F. Segor, A. Buller, M. Kollmann

Proceedings Volume 12740, 1274003 (2023) https://doi.org/10.1117/12.2680142

KEYWORDS: Reconnaissance, Sensors, Evolutionary algorithms, Autonomous vehicles, Unmanned aerial vehicles, Fermium, Reconnaissance systems, Frequency modulation, Detection and tracking algorithms, Artificial intelligence

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Proceedings Article | 31 May 2022 Presentation + Paper

Drone detection, recognition, and assistance system for counter-UAV with VIS, radar, and radio sensors

Thomas Müller, Heiko Widak, Matthias Kollmann, Aleksej Buller, Lars Wilko Sommer, Raphael Spraul, Alexander Kröker, Ilja Kaufmann, Angelika Zube, Florian Segor, Thomas Perschke, Alina Lindner, Igor Tchouchenkov

Proceedings Volume 12096, 120960A (2022) https://doi.org/10.1117/12.2619086

KEYWORDS: Unmanned aerial vehicles, Sensors, Radar, Cameras, Visualization, Visual optics, Distance measurement, Radio optics, Laser range finders, Imaging systems

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Proceedings Article | 30 April 2019 Paper

Controlling swarm complexity: a management by objective approach

Florian Segor, Igor Tchouchenkov, Aleksej Buller, Matthias Kollmann, Wilmuth Müller

Proceedings Volume 11015, 110150R (2019) https://doi.org/10.1117/12.2518608

KEYWORDS: Sensors, Control systems, Unmanned aerial vehicles, Evolutionary algorithms, Reconnaissance, Reconnaissance systems, Visualization, Process control, Unmanned vehicles, Detection and tracking algorithms

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