Agrotecnio aims to become a reference in Europe addressing all the key elements of the food production chain in an integrated way focusing on target crops and animals of commercial importance, rather than model systems. This later aspect sets our centre apart from other centers which focus on fundamental science and/or model plant and animal systems. As a result we should be able to address fundamental and important questions in the crop/animal of interest and results from our research will be directly and immediately applicable to our target organism. [Més informació]
Browsing Agrotecnio Center by Subject "3D point cloud registration"
(Institute of Electrical and Electronics Engineers, 2021-11-18) Guevara, Javier; Gené Mola, Jordi; Gregorio López, Eduard; Auat Cheein, Fernando A.
The use of three-dimensional registration techniques is an important component for sensor-based localization and mapping. Several approaches have been proposed to align three-dimensional data, obtaining meaningful results in structured scenarios. However, the increased use of high-frame-rate 3D sensors has lead to more challenging application scenarios here the performance of registration techniques may degrade significantly. In order to improve the accuracy of the procedure, different works have considered a representative subset of points while preserving application-dependent features for registration. In this work, we tackle such a problem, considering the use of a general feature-extraction operator in the spectral domain as a prior step to the registration. The proposed spectral strategies use three wavelet transforms that are evaluated along with four well-known registration techniques. The methodology was experimentally validated in a dense orchard environment. The results show that the probability of failure in registration can be reduced up to 12.04% for the evaluated approaches, leading to a significant increase in the localization accuracy. Those results validate the effectiveness and efficiency of the spectral-assisted registration algorithms in an agricultural setting and motivate their usage for a wider range of applications.