This paper presents the overview and preliminary results of the HEKTOR - Heterogeneous Autonomous Robotic System in Viticulture and Mariculture project. HEKTOR is divided into two main parts, each dealing with specific scenarios in viticulture and mariculture. The robots used in the project and each specific scenario considered are presented. In viticulture, this includes vineyard surveillance, spraying and bud rubbing using an all-terrain mobile manipulator and unmanned aerial vehicle (UAV). In mariculture, scenarios include coordinated monitoring of fish net cages from below the surface and from the air, using the UAV, an unmanned surface vehicle (USV) and a remotely operated underwater vehicle (ROV).

Underwater cultural heritage sites are subject to constant change, whether due to natural forces such as sediments, waves, currents or human intervention. Until a few decades ago, the documentation and research of these sites was mostly done manually by diving archaeologists. This paper presents the results of the integration of remote sensing technologies with autonomous marine vehicles in order to make the task of site documentation even faster, more accurate, more efficient and more precisely georeferenced. It includes the integration of multibeam sonar, side scan sonar and various cameras into autonomous surface and underwater vehicles, remotely operated vehicle and unmanned aerial vehicle. In total, case studies for nine underwater cultural heritage sites around the Mediterranean region are presented. Each case study contains a brief archaeological background of the site, the methodology of using autonomous marine vehicles and sensors for their documentation, and the results in the form of georeferenced side-scan sonar mosaics, bathymetric models or reconstructed photogrammetric models. It is important to mention that this was the first time that any of the selected sites were documented with sonar technologies or autonomous marine vehicles. The main objective of these surveys was to document and assess the current state of the sites and to establish a basis on which future monitoring operations could be built and compared. Beyond the mere documentation and physical preservation, examples of the use of these results for the digital preservation of the sites in augmented and virtual reality are presented.

Plitvice Lakes National Park is the largest national park in Croatia and also the oldest from 1949. It was added to the UNESCO World Natural Heritage List in 1979, due to the unique physicochemical and biological conditions that have led to the creation of 16 named and several smaller unnamed lakes, which are cascading one into the next. Previous scientific research proved that the increased amount of dissolved organic matter (pollution) stops the travertine processes on Plitvice Lakes. Therefore, this complex, dynamic but also fragile geological, biological and hydrological system required a comprehensive limnological survey. Thirteen of the sixteen lakes mentioned above were initially surveyed from the air by an unmanned aircraft equipped with a survey grade GNSS and a full frame high-resolution full-screen camera. From these recordings, a georeferenced, high-resolution orthophoto was generated, on which the following surveys by a multibeam sonar depended. It is important to mention that this was the first time that these lakes had ever been surveyed both with the multibeam sonar technique and with such a high-resolution camera. Due to the fact that these thirteen lakes are difficult to reach and often too shallow for a boat-mounted sonar, a special autonomous surface vehicle was developed. The lakes were surveyed by the autonomous surface vehicle mounted with a multibeam sonar to create detailed bathymetric models of the lakes. The missions were planned for the surface vehicle based on the orthophoto from the preliminary studies. A detailed description of the methodology used to survey the different lakes is given here. In addition, the resulting high-resolution bathymetric maps are presented and analysed together with an overview of average, maximum depths and number of data points. Numerous interesting depressions, which are phenomena consistent with previous studies of Plitvice Lakes, are noted at the lake beds and their causes are discussed. This study shows the huge potential of remote sensing technologies integrated into autonomous vehicles in terms of much faster surveys, several orders of magnitude more data points (compared to manual surveys of a few decades ago), as well as data accuracy, precision and georeferencing.

Side-scan sonar mapping of an unknown large-scale seafloor area by a marine vehicle is nowadays very common. It is also important that a-priori unknown interesting parts of the seafloor area are scanned in more detail, i.e. sonified from both sides. However, completely autonomous and time-efficient coverage path (re)planning for such missions is still an open issue. In contrast to the standard overlap-all-sonar-ranges lawnmower pattern offline static coverage problem solution for side-scan sonar missions, in this paper two online sonar data-driven coverage algorithms are proposed as extensions of authors’ prior work. Analytical upper and lower bounds on performance of the proposed coverage planning algorithms are given and validated through extensive mission parameters variation simulations. Statistical performance analysis of the proposed coverage planning algorithms’ performance shows significant complete coverage time efficiency improvements w.r.t. the classical unadaptive lawnmower approach. Also, a detailed comparison of coverage planning algorithms proposed by the authors so far is provided.

A modular measurement model Extended Kalman filter (EKF) for for unmanned underwater vehicle (UUV) localization is proposed. Except for using measurements from UUV’s sensors, this EKF is augmented by ultra-short baseline range and visual-data based localization from an unmanned surface vehicle, and in-sonar image estimated UUV position. It is shown that the proposed EKF significantly enhances UUV’s navigational accuracy through a collaborative fusion of sensor data from multiple heterogeneous marine vehicles. Also, an Extended Rauch-Tung-Striebel (ERTS) smoother was run aposteriori to further improve UUV’s localization, which is shown to be very useful for accurate post-processing of the data acquired by the UUV.

Mapping an unknown large-scale marine area by a side-scan sonar onboard a marine vehicle as quickly as possible is often of great importance. It is also important that a-priori unknown interesting parts of the area are scanned in more detail, i.e. with the removal of sonic shadows. In contrast to the standard overlap-all-sonar-ranges lawnmower pattern, which is an offline static coverage problem solution for side-scan sonar missions, here a novel online side-scan sonar data-driven coverage solution is proposed. The proposed coverage algorithm provides a coverage solution based on local information gain from side-scan sonar data. At the same time, the solution is generated in such a way that coverage path length is minimized while covering the same area as the standard lawnmower. Upper and lower bounds of the proposed algorithm's improvement compared to the overlap-all-sonar-ranges lawnmower method are estimated analytically and validated through extensive mission parameters variation simulations. Simulation results show that our approach can cut down coverage path length significantly compared to the standard lawnmower method in most application cases.