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Cyrill Stachniss

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Cyrill Stachniss is a full professor for photogrammetry at the University of Bonn and the deputy managing director of the Institute of Geodesy and Geoinformation. Before working in Bonn, he was a lecturer at the University of Freiburg in Germany, a guest lecturer at the University of Zaragoza in Spain, and a senior researcher at the Swiss Federal Institute of Technology in the group of Roland Siegwart. Cyrill Stachniss finished his habilitation in 2009 and received his PhD thesis entitled “Exploration and Mapping with Mobile Robots” supervised by Wolfram Burgard at the University of Freiburg in 2006. From 2008-2013, he was an associate editor of the IEEE Transactions on Robotics, since 2010 a Microsoft Research Faculty Fellow, and received the IEEE RAS Early Career Award in 2013. Since 2015, he is a senior editor for the IEEE Robotics and Automation Letters. Cyrill Stachniss is actively participating in European research projects in the context of urban navigation, precision farming, factories of the future, and digital access to cultural heritage. Has was the coordinator of the EC-funded project "ROVINA" for digitizing the Roman catacombs with robots and is the speaker of the DFG research unit "Mapping on Demand". In his research, he focuses on probabilistic techniques in the context of mobile robotics, navigation, and visual perception. Central areas of his research are agricultural robotics, computer-controlled cars, and unmanned aerial vehicles. In sum, he has coauthored over 160 publications.

Crops are key for a sustainable food production and we face several challenges in crop production. First, we need to feed a growing world population. Second, our society demands high-quality foods. Third, we have to reduce the amount agrochemicals that we apply to our fields as it directly affects our ecosystem. Precision farming techniques offer a great potential to address these challenges, but we have to acquire and provide the relevant information about the field status to the farmers such that specific actions can be taken.

This paper won the IEEE Robotics & Automation Best Automation Paper Award at ICRA 2017.