Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2015
Abstract
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Authors
Katarzyna Dabrowska – Zielinska Piotr Goliński Marit Jørgensen Jørgen A.B. Mølmann Gregory Taff Monika Tomaszewska Barbara Golińska Maria Budzynska Martyna GatkowskaAbstract
No abstract has been registered
Authors
John Marshall BrydenAbstract
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Authors
Daniel RasseAbstract
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Authors
Kjell Andreassen Wenche AasAbstract
No abstract has been registered
Authors
Per Stålnacke Annelene Pengerud Anatoli Vassiljev Erik Smedberg Carl-Magnus Mörth Hanna Eriksson Hägg Christoph Humborg Hans Estrup AndersenAbstract
No abstract has been registered
Abstract
Vehicles which operate in agricultural row crops, need to strictly follow the established wheel tracks. Errors in navigation where the robot sways of its path with one or more wheels may damage the crop plants. The specific focus of this paper is on an agricultural robot operation in row cultures. The robot performs machine vision detecting weeds within the crop rows and treats the weeds by high precision drop-on-demand application of herbicide. The navigation controller of the robot needs to follow the established wheel tracks and minimize the camera system offset from the seed row. The problem has been formulated as a Nonlinear Model Predictive Control (NMPC) problem with the objective of keeping the vision modules centered over the seed rows, and constraining the wheel motion to the defined Wheel tracks. The system and optimization problem has been implemented in Python using the Casadi framework. The implementation has been evaluated through simulations of the system, and compared with a PD controller. The NMPC approach display advantages and better performance when facing the path constraints of operating in row crops.
Abstract
Vehicles which operate in agricultural row crops, need to strictly follow the established wheel tracks. Errors in navigation where the robot sways of its path with one or more wheels may damage the crop plants. The specific focus of this paper is on an agricultural robot operation in row cultures. The robot performs machine vision detecting weeds within the crop rows and treats the weeds by high precision drop-on-demand application of herbicide. The navigation controller of the robot needs to follow the established wheel tracks and minimize the camera system offset from the seed row. The problem has been formulated as a Nonlinear Model Predictive Control (NMPC) problem with the objective of keeping the vision modules centered over the seed rows, and constraining the wheel motion to the defined Wheel tracks. The system and optimization problem has been implemented in Python using the Casadi framework. The implementation has been evaluated through simulations of the system, and compared with a PD controller. The NMPC approach display advantages and better performance when facing the path constraints of operating in row crops.
Abstract
High northern latitudes are increasingly exposed to the combination of extreme winter climate and deposition of long-distance dispersed nitrogen pollution. These combined pressures may over time drive changes in plant composition and carbon uptake.