Thomas Ziegler

ETH Zurich, Board of the Swiss Federal Institutes of Technology

Papers

Total Citations

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About

Thomas Ziegler is a robotics researcher whose work bridges multi-agent perception and autonomous manipulation, with a focus on enabling robots to operate reliably in unstructured environments. His key research areas include distributed formation estimation, collaborative simultaneous localization and mapping (SLAM), and robotic cloth manipulation. Ziegler’s most cited work, “Distributed Formation Estimation Via Pairwise Distance Measurements” (2021, 42 citations), addresses a fundamental challenge in swarm robotics: continuously estimating the relative configuration of robot teams in real time without relying on external positioning systems like GPS. This contribution is critical for scalable, infrastructure-free autonomy in multi-robot systems. In “COVINS: Visual-Inertial SLAM for Centralized Collaboration” (2021), he advanced collaborative SLAM, enabling multiple agents to co-localize and jointly map environments—a key enabler for multi-robot perception and augmented reality applications. His work on cloth manipulation (2022) applies deep learning to category classification and landmark detection, tackling the notoriously difficult problem of robotic fabric handling. Ziegler’s research has been cited over 50 times, reflecting its growing impact on both theoretical foundations and practical deployments in robotics.