Effective Target Aware Visual Navigation for UAVs

In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast maneuvers) do not allow to constantly maintain the line of sight with a target of interest. Instead, we compute the optimal trajectory by solving a non-linear optimization problem that minimizes the target re-projection error while meeting the UAV's dynamic constraints. The desired trajectory is then tracked by means of a real-time Non-linear Model Predictive Controller (NMPC): this implicitly allows the multirotor to satisfy both the required constraints. We successfully evaluate the proposed approach in many real and simulated experiments, making an exhaustive comparison with a standard approach.Comment: Conference paper at "European Conference on Mobile Robotics" (ECMR) 201

Plane extraction for indoor place recognition

In this paper, we present an image based plane extraction method well suited for real-time operations. Our approach exploits the assumption that the surrounding scene is mainly composed by planes disposed in known directions. Planes are detected from a single image exploiting a voting scheme that takes into account the vanishing lines. Then, candidate planes are validated and merged using a region grow- ing based approach to detect in real-time planes inside an unknown in- door environment. Using the related plane homographies is possible to remove the perspective distortion, enabling standard place recognition algorithms to work in an invariant point of view setup. Quantitative Ex- periments performed with real world images show the effectiveness of our approach compared with a very popular method

An Effective Multi-Cue Positioning System for Agricultural Robotics

The self-localization capability is a crucial component for Unmanned Ground Vehicles (UGV) in farming applications. Approaches based solely on visual cues or on low-cost GPS are easily prone to fail in such scenarios. In this paper, we present a robust and accurate 3D global pose estimation framework, designed to take full advantage of heterogeneous sensory data. By modeling the pose estimation problem as a pose graph optimization, our approach simultaneously mitigates the cumulative drift introduced by motion estimation systems (wheel odometry, visual odometry, ...), and the noise introduced by raw GPS readings. Along with a suitable motion model, our system also integrates two additional types of constraints: (i) a Digital Elevation Model and (ii) a Markov Random Field assumption. We demonstrate how using these additional cues substantially reduces the error along the altitude axis and, moreover, how this benefit spreads to the other components of the state. We report exhaustive experiments combining several sensor setups, showing accuracy improvements ranging from 37% to 76% with respect to the exclusive use of a GPS sensor. We show that our approach provides accurate results even if the GPS unexpectedly changes positioning mode. The code of our system along with the acquired datasets are released with this paper.Comment: Accepted for publication in IEEE Robotics and Automation Letters, 201

Non-Linear Model Predictive Control with Adaptive Time-Mesh Refinement

In this paper, we present a novel solution for real-time, Non-Linear Model Predictive Control (NMPC) exploiting a time-mesh refinement strategy. The proposed controller formulates the Optimal Control Problem (OCP) in terms of flat outputs over an adaptive lattice. In common approximated OCP solutions, the number of discretization points composing the lattice represents a critical upper bound for real-time applications. The proposed NMPC-based technique refines the initially uniform time horizon by adding time steps with a sampling criterion that aims to reduce the discretization error. This enables a higher accuracy in the initial part of the receding horizon, which is more relevant to NMPC, while keeping bounded the number of discretization points. By combining this feature with an efficient Least Square formulation, our solver is also extremely time-efficient, generating trajectories of multiple seconds within only a few milliseconds. The performance of the proposed approach has been validated in a high fidelity simulation environment, by using an UAV platform. We also released our implementation as open source C++ code.Comment: In: 2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2018

AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming

The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve the effectiveness of robotic systems applied to precision agriculture. In this context, building and updating a common map of the field is an essential but challenging task. The maps built using robots of different types show differences in size, resolution and scale, the associated geolocation data may be inaccurate and biased, while the repetitiveness of both visual appearance and geometric structures found within agricultural contexts render classical map merging techniques ineffective. In this paper we propose AgriColMap, a novel map registration pipeline that leverages a grid-based multimodal environment representation which includes a vegetation index map and a Digital Surface Model. We cast the data association problem between maps built from UAVs and UGVs as a multimodal, large displacement dense optical flow estimation. The dominant, coherent flows, selected using a voting scheme, are used as point-to-point correspondences to infer a preliminary non-rigid alignment between the maps. A final refinement is then performed, by exploiting only meaningful parts of the registered maps. We evaluate our system using real world data for 3 fields with different crop species. The results show that our method outperforms several state of the art map registration and matching techniques by a large margin, and has a higher tolerance to large initial misalignments. We release an implementation of the proposed approach along with the acquired datasets with this paper.Comment: Published in IEEE Robotics and Automation Letters, 201

Estudo da molhabilidade e das propriedades anticorrosivas de recobrimentos finos de PTFE-like/Al2O3 sobre aço carbono

O estudo da eficiência de recobrimentos que apresentam propriedades anti-corrosivas, quando aplicados em materiais metálicos, torna-se importante no ponto de vista acadêmico e industrial. Com esse intuito, foram sintetizadas amostras de aço carbono 1020 recobertas com alumina e Politetrafluoroetileno (PTFE), depositados por Radio Frequency Sputtering (RFSputtering), para o estudo das propriedades anticorrosivas e molhabilidade. A presença da alumina mostrou-se essencial frente aos estudos iniciais com silano, assim como uma afinidade sinérgica com o PTFE. Os resultados das propriedades anticorrosivas indicaram resultados promissores. A resistência à transferência de carga aumentou de 3,12 kΩcm², considerando a amostra sem recobrimento, para 101 kΩcm², para a amostra recoberta com alumina e com PTFE-like depositado por 45 minutos e os resultados das resistências dos recobrimentos, com a inserção do PTFE-like sobre a alumina subiram de 0,24 kΩcm², considerando somente o recobrimento de alumina, para 51,4 kΩcm², considerando a amostra recoberta com alumina e PTFE-like depositado por 45 minutos, quando em contato com solução durante 0,25h. Os valores de capacitância, simulados por circuito elétrico equivalente, diminuíram até duas ordens de grandeza com a inserção dos recobrimentos. As capacitâncias de dupla camada e de recobrimento caíram de 216 µFcm-2 (amostra nua) e 330 µFcm-2 (recoberta com alumina) para 1,25 µFcm-2 (recoberta com alumina e PTFE-like depositado por 15 minutos) e 2,29 µFcm-2 (recoberta com alumina e PTFE-like depositado por 30 min), respectivamente. Esses resultados indicaram uma efetiva proteção à corrosão. Os fatores que contribuíram para a proteção do substrato foram as barreiras físicas interpostas entre substrato e eletrólito e também a baixa molhabilidade, que está associada a uma baixa energia livre de Gibbs, em que os ângulos de contato Os fatores que contribuíram para a proteção do substrato foram as barreiras físicas interpostas entre substrato e eletrólito e também a baixa molhabilidade, que está associada a uma baixa energia livre de Gibbs, em que os ângulos de contato aumentaram de 90±2°, considerando a amostra sem recobrimento, para 120±2° para a amostra recoberta com alumina e PTFE-like depositado por 45 minutos. Esse aumento resultou em menos interações entre líquido/sólido. Comparando com relatos na literatura, os recobrimentos desse trabalho, tendo em conta sua resistência relativa do recobrimento por unidade de espessura, alcançaram eficiências de duas a três ordens de grandeza maiores na proteção a superfícies de aço carbono.The study of efficiency of coatings that present anti-corrosion properties, when applied to metallic surfaces, becomes is important in the academic and industrial perspectives. For that purpose, samples of commercial 1020 carbon steel coated with alumina and PTFE-like were deposited by RF-Sputtering for anti-corrosion and wettability studies, performed by Electrochemical Impedance Spectroscopy (EIS) and the Sessile drop method, respectively. Studies of morphology and topology were also performed by SEM, XPS and AFM. The insertion of the alumina coating was important, in comparison to silane, as well as to its synergistic affinity with PTFE. The charge transfer and coating resistances increased from 3.12 kΩcm² (bare steel) and 0.24 kΩcm² (alumina coating) to 101.0 kΩcm² and 51.4 kΩcm², for the sample coated with alumina and PTFE-like deposited for 45 minutes, respectively. The double layer and coatings capacitances for the coated samples, simulated by the equivalent electric circuit approach, decrease in comparison to bare steel up to two orders of magnitude. These results indicate an effective corrosion protection. The physical barrier provided by coatings and their low wettability also contributed to the corrosion protection, since contact angles increased from 90±2°, for the uncoated sample, to 120±2° for the sample coated with alumina and PTFE-like deposited for 45 minutes, resulting in less interaction in the liquid/solid interface. In comparison to literature reports, these coatings achieved efficiency two to three orders of magnitude higher in relative coating resistance, per thickness unit, in carbon steel surface protection

Multi-Spectral Image Synthesis for Crop/Weed Segmentation in Precision Farming

An effective perception system is a fundamental component for farming robots, as it enables them to properly perceive the surrounding environment and to carry out targeted operations. The most recent approaches make use of state-of-the-art machine learning techniques to learn an effective model for the target task. However, those methods need a large amount of labelled data for training. A recent approach to deal with this issue is data augmentation through Generative Adversarial Networks (GANs), where entire synthetic scenes are added to the training data, thus enlarging and diversifying their informative content. In this work, we propose an alternative solution with respect to the common data augmentation techniques, applying it to the fundamental problem of crop/weed segmentation in precision farming. Starting from real images, we create semi-artificial samples by replacing the most relevant object classes (i.e., crop and weeds) with their synthesized counterparts. To do that, we employ a conditional GAN (cGAN), where the generative model is trained by conditioning the shape of the generated object. Moreover, in addition to RGB data, we take into account also near-infrared (NIR) information, generating four channel multi-spectral synthetic images. Quantitative experiments, carried out on three publicly available datasets, show that (i) our model is capable of generating realistic multi-spectral images of plants and (ii) the usage of such synthetic images in the training process improves the segmentation performance of state-of-the-art semantic segmentation Convolutional Networks.Comment: Submitted to Robotics and Autonomous System

The expansion of exotic Chinook salmon (Oncorhynchus tshawytscha) in the extreme south of Patagonia: an environmental DNA approach

The ability to detect species at low densities, greatly improves the success of management action on alien invasive species and decreases their possible impact on ecosystems. In the last two decades, exotic Chinook salmon (Oncorhynchus tshawytscha) have established populations in both Pacific and Atlantic river basins of Patagonia. The last established populations have been reported in the extreme south of Patagonia, on the island of Tierra del Fuego (TDF). The relatively recent appearance of Chinook salmon in TDF and the great phenotypic plasticity of this species, make it necessary to study their distribution and expansion as soon as possible, since they have the potential to negatively impact on native ecosystems. With the objective of knowing the current distribution status of exotic Chinook salmon in TDF, we optimized and implemented a detection method based on environmental DNA (eDNA). First, we designed Chinook salmon-specific primers, with no cross-amplification, using DNA from other species that are living at the same environment. Second, we validated the primers in situ by detecting Chinook salmon DNA from natural environments at the same time that we performed a conventional survey using an electrofishing survey method. Finally, we collected water samples from 10 river basins and one estuary within TDF and one river basin from Isla de los Estados (IE) and performed single-species real-time PCR assays. We were able to detect Chinook salmon DNA from 5 basins and from the estuary in TDF. These eDNA-based results allowed us to confirm the expansion of exotic Chinook salmon since they were first reported in TDF.Fil: Nardi, Cristina Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina. Universidad Nacional de Tierra del Fuego, Antártida e Islas del Atlántico Sur. Instituto de Ciencias Polares, Ambientales y Recursos Naturales; ArgentinaFil: Fernandez, Daniel Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina. Universidad Nacional de Tierra del Fuego, Antártida e Islas del Atlántico Sur. Instituto de Ciencias Polares, Ambientales y Recursos Naturales; ArgentinaFil: Vanella, Fabián Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Chalde, Tomás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentin

Altered Food Behavior and Cancer: A Systematic Review of the Literature

: There is evidence of an association between cancer and certain types of altered eating behaviors, including orthorexia, food cravings, and food addiction. Given the growing interest in the topic throughout the scientific community we conducted a systematic review to summarize current evidence on the development of altered food behavior, including food addiction and cancer. The Cochrane Collaboration and the Meta-analysis Of Observational Studies in Epidemiology guidelines were followed to perform this systematic review. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used to report the process and results. The structured literature search was conducted on 19 April 2022, on PubMed/Medline and Scopus, combining free-text terms and medical subject headings. A total of seven articles were included once the selection process was completed. Food craving has been associated with different types of cancer in adults and young patients, as well as with orthorexia; conversely, compulsive eating has only been explored in patients with prolactinoma treated with dopamine agonists. This systematic review explored a new area of research that warrants further investigation. More research is required to better understand the relationship between cancer and food behavior

Scritture epistemiche: progettare la didattica intrecciando tradizione e innovazione

The article describes the first year of a project called “Vertical, transpositive and epistemic writings” (Indire and UniTo), whose goal is based on focusing on new forms of writing in the school environment. Over time, the approach to new technologies has oriented the use of various “written” production methods, intertwining different media languages: these are combinations ofwords, sounds, images, already present in the technologies themselves, partly of “scriptural ideas fruit of the creativity of millennials. The project intends to consider the previous thirty years of the web, the actuality and the gap of writing “inside” and “outside” the school in the perspective of a varied and effective capacity for expression. This can happen thanks to a conscious approach and to a fruitful collaboration between students, teachers and the community of the web, through playful, poetic, ironic and autobiographical methods, among others. It is therefore not a “writing workshop”, but a path of awareness of the self and the other that can guide the choices of teachers and students. This path can allow, at the same time, personal/individual development, but also group and community. Media education must therefore undertake to monitor the sudden changes in the expressive behaviors of young people, accompanying these paths aimed at developing media/digitalskills useful for their future life projects.L’articolo descrive il primo anno di un progetto denominato “Scritture verticali, traspositive ed epistemiche” (Indire e UniTo), il cui obiettivo si basa sulla focalizzazione di nuove forme di scrittura in ambito scolastico. L’approccio alle nuove tecnologie ha orientato nel tempo l’utilizzo di varie modalità di produzione “scritta”, intrecciando differenti linguaggi mediali: combinazioni di parole, suoni, immagini in “idee scritturali” generate da nuovi ambienti comunicativi ed dalla creatività dei millennials. Il progetto intende considerare il pregresso di trent’anni di web, l’attualità e il divario della scrittura “dentro” e “fuori” la scuola, nella prospettiva di una variegata ed efficace capacità di espressione. Ciò può avvenire grazie a un approccio consapevole e a una proficua collaborazione tra allievi, insegnanti e nuove strumentazioni, attraverso modalità, tra le altre, ludiche, poetiche, ironiche e autobiografiche. Non si tratta quindi di un “laboratorio di scrittura”, ma di un percorso di consapevolezza del sé e dell’altro che possa orientare le scelte di insegnanti e alunni. Tale percorso può consentire, allo stesso tempo, uno sviluppo personale/individuale, ma anche gruppale e comunitario. La media education si impegna a monitorare i cambiamenti repentini delle condotte espressive dei ragazzi, accompagnando questi percorsi orientati allo sviluppo di competenze mediali/digitali utili ai loro futuri progetti di vita