2018

  • A. Milioto and C. Stachniss. Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics using CNNs. In Workshop on Perception, Inference, and Learning for Joint Semantic, Geometric, and Physical Understanding, International Conference on Robotics and Automation (ICRA), 2018. PDF
  • A. Milioto, P. Lottes and C. Stachniss. Real-time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs. In International Conference on Robotics and Automation (ICRA), 2018. PDF
  • Abhinav Valada, Noha Radwan and Wolfram Burgard. Deep Auxiliary Learning for Visual Localization and Odometry. In International Conference on Robotics and Automation (ICRA), 2018. PDF
  • Ciro Potena, Bartolo Della Corte, Daniele Nardi, Giorgio Grisetti and Alberto Pretto. Non-Linear Model Predictive Control with Adaptive Time-Mesh Refinement. In International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR), 2018. PDF
  • Takahiro Miki, Marija Popovic, Abel Gawel, Gregory Hitz and Roland Siegwart. Multi-agent Time-based Decision-making for the Search and Action Problem. In International Conference on Robotics and Automation (ICRA), 2018. PDF
  • L. Luft, A. Schaefer, T. Schubert and W. Burgard. Detecting Changes in the Environment Based on Full Posterior Distributions Over Real-Valued Grid Maps. IEEE Robotics and Automation Letters (RAL), vol. 3 no. 2, pages 1299-1305, 2018. PDF
  • I. Sa, Z. Chen, M. Popovic, R. Khanna, F. Liebisch, J. Nieto and R. Siegwart. weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming. IEEE Robotics and Automation Letters (RAL), vol. 3 no. 1, pages 588-595, January 2018. PDF
  • Miguel de la Iglesia Valls, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart, Fabio Vito Meier, Inkyu Sa, Renaud Dubé, Abel Roman Gawel, Mathias Bürki and Roland Siegwart. Design of an Autonomous Racecar: Perception, State Estimation and System Integration. In International Conference on Robotics and Automation (ICRA), 2018. PDF Best Student Paper Award.
  • A. Schaefer, L. Luft and W. Burgard. DCT Maps: Compact Differentiable Lidar Maps Based on the Cosine Transform. IEEE Robotics and Automation Letters (RAL), vol. 3 no. 2, pages 1002-1009, 2018. PDF

2017

  • Z. Chen, F. Maffra and I. Sa. Only Look Once, Mining Distinctive Landmarks from ConvNet for Visual Place Recognition. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF
  • M. Di Cicco, C. Potena, G. Grisetti and A. Pretto. Automatic Model Based Dataset Generation for Fast and Accurate Crop and Weeds Detection. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF
  • C. Potena, D. Nardi and A. Pretto. Effective Target Aware Optimal Visual Navigation for UAVs. In The European Conference on Mobile Robotics (ECMR), 2017. PDF
  • J. Hwangbo, I. Sa, R. Siegwart and M. Hutter. Control of a Quadrotor With Reinforcement Learning. IEEE Robotics and Automation Letters (RAL), vol. 2 no. 4, pages 2096-2103, 2017. [DOI]
  • D. Albani, D. Nardi and T. Vito. Field Coverage and Weed Mapping by UAV Swarms. In International Conference on Intelligent Robots and Systems (IROS), 2017.
  • Florian Kraemer, Alexander Schaefer, Andreas Eitel, Johan Vertens and Wolfram Burgard. From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields. In International Conference on Intelligent Robots and Systems (IROS) Workshop, Agri-Food Robotics, 2017. PDF
  • R. Khanna, I. Sa, J. Nieto and R. Siegwart. On field radiometric calibration for multispectral cameras. In International Conference on Robotics and Automation (ICRA), 2017. PDF
  • A. Milioto, P. Lottes and C. Stachniss. Real-time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs. arXiv preprint:1709.06764, 2017. PDF
  • Lukas Luft, Alexander Schaefer, Tobias Schubert and Wolfram Burgard. Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF
  • C. Müller-Ruh, F. Liebisch, J. Pfeifer and A. Walter. Investigation of ground based and airborne spectral information for Nitrogen fertilizer application optimization in sugar beet. Bornimer Agrartechnische Berichte, vol. 90, 2017.
  • I. Sa, M. Kamel, M. Burri, M. Bloesch, R. Khanna, M. Popovic, J. Nieto and R. Siegwart. Build your own visual-inertial odometry aided cost-effective and open-source autonomous drone. ArXiv e-prints, 2017. http://adsabs.harvard.edu/abs/2017arXiv170806652S.
  • H. Sommer, R. Khanna, I. Gilitschenski, Z. Taylor, R. Siegwart and J. Nieto. A Low-Cost System for High-Rate, High-Accuracy Temporal Calibration for LIDARs and Cameras. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF
  • N. Chebrolu, P. Lottes, A. Schaefer, W. Winterhalter, W. Burgard and C. Stachniss. Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields. The Internatiounal Journal of Robotics Research (IJRR), 2017. PDF [DOI]
  • F. Fleckenstein, C. Dornhege and W. Burgard. Efficient Path Planning for Mobile Robots with Adjustable Wheel Positions. In International Conference on Robotics and Automation (ICRA), 2017. PDF
  • A. Schaefer, L. Luft and W. Burgard. An Analytical Lidar Sensor Model Based on Ray Path Information. IEEE Robotics and Automation Letters (RAL), 2017. [DOI]
  • M. Popovic, G. Hitz, J. Nieto, I. Sa, R. Siegwart and E. Galceran. Online Informative Path Planning for Active Classification Using UAVs. In International Conference on Robotics and Automation (ICRA). IEEE, 2017. PDF
  • P. Lottes and C. Stachniss. Semi-Supervised Online Visual Crop and Weed Classification in Precision Farming Exploiting Plant Arrangement. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF
  • P. Lottes, R. Khanna, J. Pfeifer, R. Siegwart and C. Stachniss. UAV-Based Crop and Weed Classification for Smart Farming. In International Conference on Robotics and Automation (ICRA), 2017. PDF
  • I. Sa, M. Kamel, R. Khanna, M. Popovic, J. Nieto and R. Siegwart. Dynamic System Identification, and Control for a cost effective open-source VTOL MAV. In Field and Service Robotics, 2017. PDF
  • A. Milioto, P. Lottes and C. Stachniss. Real-time Blob-wise Sugar Beets vs Weeds Classification for Monitoring Fields using Convolutional Neural Networks. In ISPRS Conference on Unmanned Aerial Vehicles in Geomatics (UAV-g), 2017. PDF
  • A. R. Vetrella, I. Sa, M. Popovic, R. Khanna, J. Nieto, G. Fasano, D. Accardo and R. Siegwart. Improved Tau-Guidance and Vision-aided Navigation for Robust Autonomous Landing of UAVs. In Field and Service Robotics, 2017. PDF
  • M. Popovic, T. Vidal Calleja, G. Hitz, I. Sa, R. Siegwart and J. Nieto. Multiresolution Mapping and Informative Path Planning for UAV-based Terrain Monitoring. In International Conference on Intelligent Robots and Systems (IROS), 2017. PDF

2016

  • J. Schneider, C. Stachniss and W. Förstner. On the Accuracy of Dense Fisheye Stereo. IEEE Robotics and Automation Letters, vol. 1 no. 1, pages 227-234, 2016. PDF
  • P. Lottes, M. Hoeferlin, S. Sander, M. Müter, P. Schulze-Lammers and C. Stachniss. An Effective Classification System for Separating Sugar Beets and Weeds for Precision Farming Applications. In IEEE International Conference on Robotics & Automation (ICRA), 2016. PDF
  • M. Popovic, G. Hitz, J. Nieto, R. Siegwart and E. Galceran. Online Informative Path Planning for Active Classification on UAVs. arXiv preprint arXiv:1606.08164, 2016. PDF
  • J. Schneider, C. Eling, L. Klingbeil, H. Kuhlmann, C. Stachniss and others. Fast and effective online pose estimation and mapping for UAVs. In IEEE International Conference on Robotics & Automation (ICRA), pages 4784-4791. IEEE, 2016. PDF
  • F. Liebisch, J. Pfeifer, R. Khanna, P. Lottes, C. Stachniss, T. Falck, S. Sander, R. Siegwart, A. Walter and E. Galceran. Flourish-A robotic approach for automation in crop management. 22. Workshop Computer-Bildanalyse und Unbemannte autonom fliegende Systeme in der Landwirtschaft, 2016. PDF
  • C. Potena, D. Nardi and A. Pretto. Fast and Accurate Crop and Weed Identification with Summarized Train Sets for Precision Agriculture. In International Conference on Intelligent Autonomous Systems (IAS), 2016.
  • J. Pfeifer, R. Khanna, D. Constantin, M. Popovic, E. Galceran, N. Kirchgessner, A. Walter, R. Siegwart and F. Liebisch. Towards automatic UAV data interpretation for precision farming. In International Conference of Agricultural Engineering (CIGR-AgEng), 2016. PDF

2015

  • R. Khanna, M. Moller, J. Pfeifer, F. Liebisch, A. Walter and R. Siegwart. Beyond point clouds - 3D mapping and field parameter measurements using UAVs. In Emerging Technologies & Factory Automation (ETFA), 2015 IEEE 20th Conference on, pages 1-4. IEEE, 2015. PDF
  • M. Imperoli and A. Pretto. D2CO: Fast and Robust Registration of 3D Textureless Objects using the Directional Chamfer Distance. In Proc. of: 10th International Conference on Computer Vision Systems, pages 316-328, 2015. PDF
  • R. Khanna, J. Rehder, M. Möller, E. Galceran and R. Siegwart. Studying Phenotypic Variability in Crops using a Hand-held Sensor Platform. In IROS Workshop on Agri-Food Robotics, 2015. PDF