Agricultural robotics has been a popular subject in recent years from an academic as well as a commercial point of view. This is because agricultural robotics addresses critical issues such as seasonal shortages in manual labor, e.g., during harvest, as well as the increasing concern regarding environmentally friendly practices. On one hand, several individual agricultural robots have already been developed for specific tasks (e.g., for monitoring, spraying, harvesting, transport, etc.) with varying degrees of effectiveness. On the other hand, the use of cooperative teams of agricultural robots in farming tasks is not as widespread; yet, it is an emerging trend. This paper presents a comprehensive overview of the work carried out so far in the area of cooperative agricultural robotics and identifies the state-of-the-art. This paper also outlines challenges to be addressed in fully automating agricultural production; the latter is promising for sustaining an increasingly vast human population, especially in cases of pandemics such as the recent COVID-19 pandemic.

Nowadays, the necessity of heritage documentation is essential for monitoring, maintenance, and understanding needed for conservation. The survey phase has been considerably improved using cutting-edge technologies such as Unmanned Aerial Vehicles (UAV) and Terrestrial Laser Scanners (TLS). Both of these technologies have been applied in heritage documentation individually or combined. Heritage documentation in a post-natural disaster is a situation that requires rapid data acquisition on a hazardous field. On 12th of June 2017 an earthquake (Mw = 6.3), south of Lesvos island, Greece occurred, which was devastating for the Vrisa village destroying, among many other buildings the main church. The Greek State decided from the first moment to restore the whole village, which was proclaimed as a “traditional settlement” since 2002, in its original place starting from the church and the school due to the symbolic meaning that those have to a local community. For this purpose, a 3D model of the church was requested by the authorities for damage assessment. In this paper TLS and UAV photogrammetry has been used in an integrated design to rapidly facilitate the acquisition of the whole church, eliminating all possible occlusions. The TLS was exploited for the acquisition of the facades while the UAV was used for the acquisition of the roof. The recent improvement of the post-processing algorithms provided the ability to implement the fusion of TLS and UAV models and deliver an accurate 3D model of the whole church the same day that the survey was conducted.

In this paper, a novel method to modify color images for the protanopia and deuteranopia color vision deficiencies is proposed. The method admits certain criteria, such as preserving image naturalness and color contrast enhancement. Four modules are employed in the process. First, fuzzy clustering-based color segmentation extracts key colors (which are the cluster centers) of the input image. Second, the key colors are mapped onto the CIE 1931 chromaticity diagram. Then, using the concept of confusion line (i.e., loci of colors confused by the color-blind), a sophisticated mechanism translates (i.e., removes) key colors lying on the same confusion line to different confusion lines so that they can be discriminated by the color-blind. In the third module, the key colors are further adapted by optimizing a regularized objective function that combines the aforementioned criteria. Fourth, the recolored image is obtained by color transfer that involves the adapted key colors and the associated fuzzy clusters. Three related methods are compared with the proposed one, using two performance indices, and evaluated by several experiments over 195 natural images and six digitized art paintings. The main outcomes of the comparative analysis are as follows. (a) Quantitative evaluation based on nonparametric statistical analysis is conducted by comparing the proposed method to each one of the other three methods for protanopia and deuteranopia, and for each index. In most of the comparisons, the Bonferroni adjusted p-values are <0.015, favoring the superiority of the proposed method. (b) Qualitative evaluation verifies the aesthetic appearance of the recolored images. (c) Subjective evaluation supports the above results.

Geoinformatics plays an essential role during the recovery phase of a post-earthquake situation. The aim of this paper is to present the methodology followed and the results obtained by the utilization of Unmanned Aircraft Systems (UASs) 4K-video footage processing and the automation of geo-information methods targeted at both monitoring the demolition process and mapping the demolished buildings. The field campaigns took place on the traditional settlement of Vrisa (Lesvos, Greece), which was heavily damaged by a strong earthquake (Mw=6.3) on June 12th, 2017. For this purpose, a flight campaign took place on 3rd February 2019 for collecting aerial 4K video footage using an Unmanned Aircraft. The Structure from Motion (SfM) method was applied on frames which derived from the 4K video footage, for producing accurate and very detailed 3D point clouds, as well as the Digital Surface Model (DSM) of the building stock of the Vrisa traditional settlement, twenty months after the earthquake. This dataset has been compared with the corresponding one which derived from 25th July 2017, a few days after the earthquake. Two algorithms have been developed for detecting the demolished buildings of the affected area, based on the DSMs and 3D point clouds, correspondingly. The results obtained have been tested through field studies and demonstrate that this methodology is feasible and effective in building demolition detection, giving very accurate results (97%) and, in parallel, is easily applicable and suit well for rapid demolition mapping during the recovery phase of a post-earthquake scenario. The significant advantage of the proposed methodology is its ability to provide reliable results in a very low cost and time-efficient way and to serve all stakeholders and national and local organizations that are responsible for post-earthquake management.

Cultural heritage is an integral part of history and in order to better preserve, manage and highlight our cultural heritage it is necessary to first proceed to digitize and document it. Geometric documentation of a cultural heritage asset is the process of collecting, processing, rendering, and recording data to determine the location and actual form, shape, and size of a monument in three-dimensional space at a given time. This chapter presents the modern methods and technologies for the 3D acquisition of cultural heritage assets and discusses the related challenges and risks. Moreover, we are presenting the possible quality aspects observed in the fieldwork that arise from the equipment, the environmental conditions that prevail during the surveying, the object itself, the personnel expertise and the stakeholder conditions.