The objective of this research was to explore the use of data information of a low-cost IMU to provide an attitude angle with acceptable accuracy for agricultural robot navigation. This work was an attempt to create attitude angle estimation system via sensor fusion method based on gyroscope and accelerometer in this low-cost IMU. The used algorithm processed and integrated the data from triple gyroscope and tri-axis accelerometer using a low-pass filter and Kalman filter. Under this algorithm, experiment data showed that the estimation precision was improved effectively. It can solve noise jamming, and realize attitude angle optimal estimation.
In this paper is proposed to conduct a first stage AKIS diagnostic exercise developing a map of the system of the actors involved in water quality protection and catchment management that interact with the farming community. Specifically we will use the...
L’herbe pâturée est l’aliment qui coûte le moins cher dans une ration et la bonne gestion de l’herbe passe entre autre par une connaissance des quantités disponibles. Afin de simplifier et d’automatiser ces mesures d’herbe, et ainsi contribuer au maintien voire...
In the AgriSpin project (2015-2017) fifteen organisations involved in innovation support tried to understand better how each of them made a difference in helping farmers to innovate. In principle, each partner organisation hosted a Cross Visits of 3 – 4...
L’une des avancées les plus importantes dans le domaine de l’observation de la terre est la découverte des indices spectraux, ils ont notamment prouvé leur efficacité dans la caractérisation des surfaces agricoles, mais ils sont généralement définis de manière empirique....
For an intelligent agricultural robot to reliably operate on a large-scale farm, it is crucial to accurately estimate its pose. In large outdoor environments, 3D LiDAR is a preferred sensor. Urban and agricultural scenarios are characteristically different, where the latter...
