Laboratory for Underwater Systems and Technologies (LABUST), Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Dr. Đula Nađ
Laboratory for Underwater Systems and Technologies (LABUST), Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Marine robotics requires high quality simulators due to complexity and availability of trials at sea. While there are several simulators in the literature, these have gaps in applications requiring high visual fidelity and human-robot interaction. This paper describes Marine Robotics Unity Simulator (MARUS), an open-source simulator for marine robotics based on Unity3D software that aims to close those gaps. It can simulate multi-robot systems in a marine environment offering water physics and a wide array of sensors commonly used in underwater and maritime domain. An interface allowing inter-connectivity with the simulator was developed where the focus was put on ROS 1/2 integration preferred in robotics community. Due to growing requirements on high-fidelity visual simulation required for machine learning, tools were developed for enabling dataset generation with automatic annotations. Examples of simulator application demonstrate the capabilities of the simulator for real world problems encountered during research project development.
SCUBA diving activities are classified as high-risk due to the dangerous environment, dependency on technical equipment that ensures life support, reduced underwater navigation and communication capabilities all of which compromise diver safety. While autonomous underwater vehicles (AUVs) have become irreplaceable tools for seabed exploration, monitoring, and mapping in various applications, they still lack the higher cognitive capabilities offered by a human diver. The research presented in this paper was carried out under the EU FP7 “CADDY—Cognitive Autonomous Diving Buddy”. It aims to take advantage of both human diver and AUV complementary traits by making their synergy a potential solution for mitigation of state of the art diving challenges. The AUV increases diver safety by constantly observing the diver, provides navigation aiding by directing the diver and offers assistance (e.g., lights, tool fetching, etc.). The control algorithms proposed in the paper provide a foundation for implementing these services. These algorithms use measurements from stereo-camera, sonar and ultra-short baseline acoustic localization to ensure the vehicle constantly follows and observes the diver. Additionally, the vehicle maintains a relative formation with the diver to allow observation from multiple viewpoints and to aid underwater navigation by pointing towards the next point of interest. Performance of the proposed algorithms is evaluated using results from pool experiments.
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.
In this paper, the path following problem of an underactuated unmanned surface vehicle (USV) in the presence of environmental disturbances is considered. To compensate for the sideslip induced by drift forces, an adaptive Kalman-like observer is proposed to estimate both the path following errors and the unknown sideslip angle. Based on the estimated angle, an adaptive observer-based line-of-sight (AO-LOS) guidance law is then constructed to ensure convergence to the desired path. It has been proven that the proposed sideslip estimator is uniformly globally exponentially stable (UGES), while the equilibrium of the cascade system, composed of the sideslip estimator and guidance law, is shown to be uniformly semiglobally exponentially stable (USGES). Several numerical and experimental examples are provided to validate the theoretical results and demonstrate the practical applicability of the AO-LOS guidance law.
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.