Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2015
Forfattere
Jan-Ole Skage Skåtøy Berit SkoglundSammendrag
Bioforsk, Norsk institutt for landbruksøkonomisk forskning og Norsk institutt for skog og landskap blir slått sammen til ett institutt fra 1. juli 2015. Instituttets nye navn er Norsk institutt for bioøkonomi (NIBIO) og blir Norges største tverrfaglige forskningsinstitutt innenfor landbruk og miljø med omkring 710 ansatte.
Forfattere
Kjell Andreassen Wenche AasSammendrag
Det er ikke registrert sammendrag
Forfattere
Per Stålnacke Annelene Pengerud Anatoli Vassiljev Erik Smedberg Carl-Magnus Mörth Hanna Eriksson Hägg Christoph Humborg Hans Estrup AndersenSammendrag
Det er ikke registrert sammendrag
Forfattere
Per Jarle MøllerhagenSammendrag
Det er ikke registrert sammendrag
Forfattere
Per Jarle MøllerhagenSammendrag
Det er ikke registrert sammendrag
Forfattere
Synnøve RivedalSammendrag
Det er ikke registrert sammendrag
Forfattere
Bjørn Egil FløSammendrag
Anmeldelse av Siri Helles Skal landet gro att? Korleis berge norsk landbruk.
Sammendrag
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.
Sammendrag
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.
Forfattere
Hilde HallandSammendrag
Det er ikke registrert sammendrag