6 research outputs found
Use of consumer-grade cameras to assess wheat N status and grain yield
Relationships between (a) fractional Intercepted PAR (fIPAR), and (b) aboveground biomass (Biomass) and (c) grain yield at harvest with the Normalized Difference Vegetation Index (NDVI) derived either from a spectroradiometer or a conventional camera at final grain filling (n = 12).Postprint (published version
Implementation and verification of a lunar mission subsystems
This final project is to implement and verify some of the subsystems that make
up the Lunar mission designed by the team FREDNET Team
(www.teamfrednet.org) for the Google Lunar X Prize, a competition to land on
the moon in 20XX, collaborating on the design of some components. This
project is developed in collaboration with other researchers of many
nationalities and therefore needs to be part of the group in a real project
focused on the use of open source software and the Internet community.
Especially important is the development of, with our collaboration, one of the
possible Rovers (vehicle that will move through the lunar surface) under the
name of Pico-Rover. Highlights its particular design, emulating a small ball. We
can develop a new concept of proposing Rovers miniaturization and cost
reduction by applying concepts of physics but unconventional or usual (by now,
all are Rovers used have low manoeuvrability and very high cost).
Especially, we have studied and developed a short-range communication to
allow the sending and receiving data to the Rover as images, video, telemetry,
etc, and accelerometers to achieve radio-control and autonomous Rover
control.
Furthermore, we proceed to the study, construction and testing of
communications boards CAN-Do for possible use in the Lunar Bus and / or
Lunar Lander, which will commented in detail later.
It has also initiated an investigation to give the Rover a system for detecting
obstacles under the name of PicoSAR (micro-RADAR). It has also studied
possible characteristics of a satellite link between the Rover and the Lunar
Lander, which allows you to be in contact with the Rover.
It is a very ambitious project, but which also allows us to participate in an
innovative and very interesting format that we can already say that we are an
important part in the team
Disseny d’un sistema d’estabilitzaciĂł de cĂ meres de baix cost mitjançant la implementaciĂł d’un “Gimbal analĂtic”
Image stabilization of photos or video is important on different applications such as search-and-rescue or electrical power line inspection. Any motion creates a change on camera orientation, which can be balanced using complex image algorithms (perspective change, resizing, etc.).
Nowadays, two opposite options have been applied. The first one, uses a complex platform with sensors and actuators that are able to, in real-time, correct non-desired motions and vibrations or aim to a specific target. They are called gimbals. They are expensive, big and heavy. The second one, uses image processing techniques (such as pattern recognition algorithms), that are able to process images until an image stabilization effect is obtained. This software approach requires powerful computers, because of the big amount of data from each frame or image. The approach presented in this project, uses an inertial sensor (IMU) connected to a CPU. It is able to, in real-time, record inertial data and in parallel, or in post-processing, correct images using this data (analytical solution). A commercial camera is used. The entire system is controlled by the CPU.
Therefore, the main purpose of the project is the design, implementation and verification of a low cost image stabilization system by implementing an analytical gimbal. The system is composed by a small and portable computer responsible of image acquisition control and synchronism. Image stabilization is done in post-processing, reducing execution time considerably if compared with image processing techniques previously commented. It works with a low cost commercial camera and a low cost IMU, reducing overall cost. To work properly, it is critical a synchronism between data and image acquisition. The system performance is verified and validated on different scenarios. Finally, the results obtained and some future improvements or possible applications are presented.CatalĂ : L’estabilitzaciĂł de seqüències d’imatges o vĂdeo Ă©s important en diferent tipus d’aplicacions com la cerca de persones o l’inspecciĂł de lĂnees elèctriques. Qualsevol moviment implica un canvi en l’orientaciĂł de la cĂ mera, requerint de rectificacions, a vegades complexes, d’imatge (com per exemple, un canvi de perspectiva). Es poden destacar dues solucions totalment oposades. Per una banda, s’han desenvolupat plataformes complexes amb sensor inercials i actuadors mecĂ nics que estabilitzen contĂnuament la cĂ mera (anomenats gimbals). Aquests sistemes acostumen a ser grans, pesats i cars. Per altra banda, hi ha una gran varietat de programaris, que per mitjĂ , exclusivament, del processat d’imatges permeten estabilitzar-les. Aquests programaris acostumen a requerir d’un elevat temps de processat i de potents ordinadors degut a la gran quantitat de dades que representa cada imatge. El projecte presenta la possibilitat de fer servir uns sensors inercials (a vegades ja presents, como en un UAV) però sense actuar sobre el moviment de la cĂ mera. Les imatges son processades i estabilitzades fent servir les dades obtingudes pels sensors inercials.
L’objectiu d’aquest projecte Ă©s dissenyar i implementar un sistema gimbal analĂtic d’estabilitzaciĂł de baix cost. El nou sistema utilitza una cĂ mera digital de consum i una unitat amb sensors inercials (IMU), ambdĂłs productes de baix cost comparats amb les solucions actuals. Un ordinador petit i de baix cost s’encarrega del control del sistema i es rectifiquen les imatges per mitjĂ del processat de les dades obtingudes pels sensors inercials (pero això es una sol·luciĂł analĂtica, a diferencia de les solucions on la rectificaciĂł fa servir tècniques de processat d’imatges o actuadors). S’aconsegueix reduir significativament els recursos requerits per al seu processat i alhora evitar els complexos sistemes d’actuadors mecĂ nics. Les tasques principals a realitzar han sigut el disseny e implementaciĂł del hardware i software necessari per a l’adquisiciĂł de les dades i posterior estabilitzaciĂł de les imatges. Per a que tot el sistema funcioni correctament, esdevĂ© clau el sincronisme de les dades entre la cĂ mera i la IMU (per això s’ha desenvolupat una estratègia per a garantir els sincronisme de les dades). Posteriorment, s’han estudiat e implementat diferents algoritmes d’orientaciĂł i rectificaciĂł d’imatges, continuant amb la verificaciĂł i validaciĂł del sistema. Finalment, s’inclouen les conclusions del treball i algunes futures millores o possibles aplicacions
Disseny d’un sistema d’estabilitzaciĂł de cĂ meres de baix cost mitjançant la implementaciĂł d’un “Gimbal analĂtic”
Image stabilization of photos or video is important on different applications such as search-and-rescue or electrical power line inspection. Any motion creates a change on camera orientation, which can be balanced using complex image algorithms (perspective change, resizing, etc.).
Nowadays, two opposite options have been applied. The first one, uses a complex platform with sensors and actuators that are able to, in real-time, correct non-desired motions and vibrations or aim to a specific target. They are called gimbals. They are expensive, big and heavy. The second one, uses image processing techniques (such as pattern recognition algorithms), that are able to process images until an image stabilization effect is obtained. This software approach requires powerful computers, because of the big amount of data from each frame or image. The approach presented in this project, uses an inertial sensor (IMU) connected to a CPU. It is able to, in real-time, record inertial data and in parallel, or in post-processing, correct images using this data (analytical solution). A commercial camera is used. The entire system is controlled by the CPU.
Therefore, the main purpose of the project is the design, implementation and verification of a low cost image stabilization system by implementing an analytical gimbal. The system is composed by a small and portable computer responsible of image acquisition control and synchronism. Image stabilization is done in post-processing, reducing execution time considerably if compared with image processing techniques previously commented. It works with a low cost commercial camera and a low cost IMU, reducing overall cost. To work properly, it is critical a synchronism between data and image acquisition. The system performance is verified and validated on different scenarios. Finally, the results obtained and some future improvements or possible applications are presented.CatalĂ : L’estabilitzaciĂł de seqüències d’imatges o vĂdeo Ă©s important en diferent tipus d’aplicacions com la cerca de persones o l’inspecciĂł de lĂnees elèctriques. Qualsevol moviment implica un canvi en l’orientaciĂł de la cĂ mera, requerint de rectificacions, a vegades complexes, d’imatge (com per exemple, un canvi de perspectiva). Es poden destacar dues solucions totalment oposades. Per una banda, s’han desenvolupat plataformes complexes amb sensor inercials i actuadors mecĂ nics que estabilitzen contĂnuament la cĂ mera (anomenats gimbals). Aquests sistemes acostumen a ser grans, pesats i cars. Per altra banda, hi ha una gran varietat de programaris, que per mitjĂ , exclusivament, del processat d’imatges permeten estabilitzar-les. Aquests programaris acostumen a requerir d’un elevat temps de processat i de potents ordinadors degut a la gran quantitat de dades que representa cada imatge. El projecte presenta la possibilitat de fer servir uns sensors inercials (a vegades ja presents, como en un UAV) però sense actuar sobre el moviment de la cĂ mera. Les imatges son processades i estabilitzades fent servir les dades obtingudes pels sensors inercials.
L’objectiu d’aquest projecte Ă©s dissenyar i implementar un sistema gimbal analĂtic d’estabilitzaciĂł de baix cost. El nou sistema utilitza una cĂ mera digital de consum i una unitat amb sensors inercials (IMU), ambdĂłs productes de baix cost comparats amb les solucions actuals. Un ordinador petit i de baix cost s’encarrega del control del sistema i es rectifiquen les imatges per mitjĂ del processat de les dades obtingudes pels sensors inercials (pero això es una sol·luciĂł analĂtica, a diferencia de les solucions on la rectificaciĂł fa servir tècniques de processat d’imatges o actuadors). S’aconsegueix reduir significativament els recursos requerits per al seu processat i alhora evitar els complexos sistemes d’actuadors mecĂ nics. Les tasques principals a realitzar han sigut el disseny e implementaciĂł del hardware i software necessari per a l’adquisiciĂł de les dades i posterior estabilitzaciĂł de les imatges. Per a que tot el sistema funcioni correctament, esdevĂ© clau el sincronisme de les dades entre la cĂ mera i la IMU (per això s’ha desenvolupat una estratègia per a garantir els sincronisme de les dades). Posteriorment, s’han estudiat e implementat diferents algoritmes d’orientaciĂł i rectificaciĂł d’imatges, continuant amb la verificaciĂł i validaciĂł del sistema. Finalment, s’inclouen les conclusions del treball i algunes futures millores o possibles aplicacions
Disseny d’un sistema d’estabilitzaciĂł de cĂ meres de baix cost mitjançant la implementaciĂł d’un “Gimbal analĂtic”
Image stabilization of photos or video is important on different applications such as search-and-rescue or electrical power line inspection. Any motion creates a change on camera orientation, which can be balanced using complex image algorithms (perspective change, resizing, etc.).
Nowadays, two opposite options have been applied. The first one, uses a complex platform with sensors and actuators that are able to, in real-time, correct non-desired motions and vibrations or aim to a specific target. They are called gimbals. They are expensive, big and heavy. The second one, uses image processing techniques (such as pattern recognition algorithms), that are able to process images until an image stabilization effect is obtained. This software approach requires powerful computers, because of the big amount of data from each frame or image. The approach presented in this project, uses an inertial sensor (IMU) connected to a CPU. It is able to, in real-time, record inertial data and in parallel, or in post-processing, correct images using this data (analytical solution). A commercial camera is used. The entire system is controlled by the CPU.
Therefore, the main purpose of the project is the design, implementation and verification of a low cost image stabilization system by implementing an analytical gimbal. The system is composed by a small and portable computer responsible of image acquisition control and synchronism. Image stabilization is done in post-processing, reducing execution time considerably if compared with image processing techniques previously commented. It works with a low cost commercial camera and a low cost IMU, reducing overall cost. To work properly, it is critical a synchronism between data and image acquisition. The system performance is verified and validated on different scenarios. Finally, the results obtained and some future improvements or possible applications are presented.CatalĂ : L’estabilitzaciĂł de seqüències d’imatges o vĂdeo Ă©s important en diferent tipus d’aplicacions com la cerca de persones o l’inspecciĂł de lĂnees elèctriques. Qualsevol moviment implica un canvi en l’orientaciĂł de la cĂ mera, requerint de rectificacions, a vegades complexes, d’imatge (com per exemple, un canvi de perspectiva). Es poden destacar dues solucions totalment oposades. Per una banda, s’han desenvolupat plataformes complexes amb sensor inercials i actuadors mecĂ nics que estabilitzen contĂnuament la cĂ mera (anomenats gimbals). Aquests sistemes acostumen a ser grans, pesats i cars. Per altra banda, hi ha una gran varietat de programaris, que per mitjĂ , exclusivament, del processat d’imatges permeten estabilitzar-les. Aquests programaris acostumen a requerir d’un elevat temps de processat i de potents ordinadors degut a la gran quantitat de dades que representa cada imatge. El projecte presenta la possibilitat de fer servir uns sensors inercials (a vegades ja presents, como en un UAV) però sense actuar sobre el moviment de la cĂ mera. Les imatges son processades i estabilitzades fent servir les dades obtingudes pels sensors inercials.
L’objectiu d’aquest projecte Ă©s dissenyar i implementar un sistema gimbal analĂtic d’estabilitzaciĂł de baix cost. El nou sistema utilitza una cĂ mera digital de consum i una unitat amb sensors inercials (IMU), ambdĂłs productes de baix cost comparats amb les solucions actuals. Un ordinador petit i de baix cost s’encarrega del control del sistema i es rectifiquen les imatges per mitjĂ del processat de les dades obtingudes pels sensors inercials (pero això es una sol·luciĂł analĂtica, a diferencia de les solucions on la rectificaciĂł fa servir tècniques de processat d’imatges o actuadors). S’aconsegueix reduir significativament els recursos requerits per al seu processat i alhora evitar els complexos sistemes d’actuadors mecĂ nics. Les tasques principals a realitzar han sigut el disseny e implementaciĂł del hardware i software necessari per a l’adquisiciĂł de les dades i posterior estabilitzaciĂł de les imatges. Per a que tot el sistema funcioni correctament, esdevĂ© clau el sincronisme de les dades entre la cĂ mera i la IMU (per això s’ha desenvolupat una estratègia per a garantir els sincronisme de les dades). Posteriorment, s’han estudiat e implementat diferents algoritmes d’orientaciĂł i rectificaciĂł d’imatges, continuant amb la verificaciĂł i validaciĂł del sistema. Finalment, s’inclouen les conclusions del treball i algunes futures millores o possibles aplicacions
Implementation and verification of a lunar mission subsystems
This final project is to implement and verify some of the subsystems that make
up the Lunar mission designed by the team FREDNET Team
(www.teamfrednet.org) for the Google Lunar X Prize, a competition to land on
the moon in 20XX, collaborating on the design of some components. This
project is developed in collaboration with other researchers of many
nationalities and therefore needs to be part of the group in a real project
focused on the use of open source software and the Internet community.
Especially important is the development of, with our collaboration, one of the
possible Rovers (vehicle that will move through the lunar surface) under the
name of Pico-Rover. Highlights its particular design, emulating a small ball. We
can develop a new concept of proposing Rovers miniaturization and cost
reduction by applying concepts of physics but unconventional or usual (by now,
all are Rovers used have low manoeuvrability and very high cost).
Especially, we have studied and developed a short-range communication to
allow the sending and receiving data to the Rover as images, video, telemetry,
etc, and accelerometers to achieve radio-control and autonomous Rover
control.
Furthermore, we proceed to the study, construction and testing of
communications boards CAN-Do for possible use in the Lunar Bus and / or
Lunar Lander, which will commented in detail later.
It has also initiated an investigation to give the Rover a system for detecting
obstacles under the name of PicoSAR (micro-RADAR). It has also studied
possible characteristics of a satellite link between the Rover and the Lunar
Lander, which allows you to be in contact with the Rover.
It is a very ambitious project, but which also allows us to participate in an
innovative and very interesting format that we can already say that we are an
important part in the team