Marco Omainska

Fraunhofer Institute for Manufacturing Engineering and Automation, The University of Tokyo

Papers

Total Citations

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About

Marco Omainska is a roboticist focused on the intersection of automation, multi-agent systems, and computer vision. His primary research areas include automated order picking for logistics, cooperative visual pursuit control, and distributed learning for robotic networks. Omainska’s most impactful work, "Towards Automated Order Picking Robots for Warehouses and Retail" (2019), has garnered 32 citations, addressing a critical bottleneck in e-commerce and supply chain automation. In his subsequent research, Omainska pioneers cooperative control strategies where multiple robots, equipped with visual sensors, collaboratively pursue and track moving targets. His 2021 paper introduces a novel networked visual motion observer, enabling robots to estimate target motion from varying perspectives. Building on this, his 2022 work advances the field by incorporating distributed Gaussian processes, allowing robots to learn unknown target motion patterns from separate datasets while maintaining coordination under intermittent visibility. These contributions are particularly significant for applications in surveillance, search-and-rescue, and autonomous warehouse logistics, where robust, decentralized perception and control are essential. Omainska’s research demonstrates a clear trajectory from foundational automation to sophisticated, learning-based multi-robot coordination, establishing him as a rising contributor to intelligent robotic systems.