Robotics and Sensing for Sustainable Crop Production - Symposium 2024

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  • čas přidán 26. 06. 2024
  • Crop farming plays an essential role in our society, providing food, feed, fiber, and fuel. We heavily rely on agricultural production, but at the same time, we need to reduce the footprint of agriculture production. Agricultural robots offer promising directions to address management challenges in agricultural fields. For that, autonomous field robots need the ability to perceive and model their environment, predict possible future developments, and make appropriate decisions in complex and changing situations. This talk will showcase recent developments in semantic perception for crop production. It will illustrate options to boost the performance of robot perception systems operating in field environments.
    This talk was given at the Hi! PARIS Symposium 2024 by Cyrill Stachniss, a full professor at the University of Bonn and heads the Photogrammetry and Robotics Lab. He is additionally a Visiting Professor in Engineering at the University of Oxford and is with the Lamarr Institute for Machine Learning and Artificial Intelligence.
    Before his appointment in Bonn, he was with the University of Freiburg and ETH Zurich. Since 2010, he has been a Microsoft Research Faculty Fellow and received the IEEE RAS Early Career Award in 2013. From 2015 to 2019, he was senior editor for the IEEE Robotics and Automation Letters. He is the spokesperson of the DFG Cluster of Excellence “PhenoRob” at the University of Bonn, together with his colleague Heiner Kuhlmann.
    His research focuses on probabilistic techniques as well as learning approaches for mobile robotics, perception, and navigation. The main application areas of his research are autonomous service robots, agricultural robotics, and self-driving cars. He has co-authored over 300 publications and has coordinated multiple large-scale research projects on the national and European levels. Besides his university involvement, he cofounded three startups: Escarda Technologies, DeepUp, and PhenoInspect.
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