Carl Gabert

Czech Technical University in Prague, Chemnitz University of Technology

Papers

Total Citations

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About

Carl Gabert is a robotics researcher whose work lies at the intersection of visual navigation, human-robot interaction, and motion planning. His most impactful contribution is the SSM-Nav system (2020, 24 citations), a novel "teach and repeat" navigation framework that leverages CNN-based visual place recognition to enable wheeled robots to autonomously retrace arbitrary routes after a single human-led demonstration. This work addresses the critical challenge of robust, long-term robot deployment in unstructured environments. Gabert has also made significant strides in humanoid robotics, developing sampling-based motion planning algorithms that integrate biophysical characteristics to generate human-like arm motions (2021, 13 citations), a key enabler for socially acceptable robot behavior. More recently, he has explored intuitive human-robot collaboration for agile manufacturing, proposing a gesture-based symbiotic programming paradigm (2022, 5 citations) that allows workers to program robots through natural body movements rather than traditional scripting. Across these contributions, Gabert demonstrates a consistent focus on making robots more autonomous, intuitive, and socially compatible—bridging the gap between industrial capability and human-centered design.