This paper presents an overview and preliminary results of the HEKTOR (Heterogeneous Autonomous Robotic System in Viticulture and Mariculture) project. An survey of applications of a heterogeneous cooperative autonomous robotic system, consisting of aerial, surface and underwater vehicles, in mariculture scenarios is presented. Target mariculture applications of the HEKTOR robotic system are autonomous fish net cage inspection (biofouling and damage detection) as well as biomass estimation. Furthermore, detailed description of the acquired autonomous vehicles is given, namely unmanned aerial vehicle and remotely operated vehicle, as well as the catamaran-shaped autonomous surface vehicle that is developed in the scope of the project.
The oxygen minimum zones (OMZs) in the Eastern Tropical Pacific (ETP) have expanded over the past 50 years, likely leading to more frequent and more intense low oxygen extreme events. This has potentially far-reaching implica- tions for e.g., the production of the climate-relevant gas nitrous oxide or the reduction of habitat for fish and zooplankton. Yet, to date our understanding of the distribution and characteristics of low oxygen extreme events in the ETP remains limited. To fill this gap, we study low oxygen extremes in the ETP using results from an eddy-resolution hindcast simulation with the coupled physical-biogeochemical model ROMS-BEC for the Pacific from 1979 to 2016. Our setup permits us to simulate oxygen variability in the ETP affected by processes on a broad range of scales, from climate modes down to mesoscale dynamics. We detect and track low oxygen extreme events in the upper 500 meters of the ETP, by ap- plying temporally constant statistical thresholds to the hindcast simulation and requiring a minimum event duration of 5 days. While most extremes last less than 10 days and are of small volumetric extent, about 15% of the extremes exist for over a month. The diversity of the long-lasting extremes is dominated by westward propagating low oxygen eddies, which are mostly generated in the near-coastal area. Superimposed inter-annual variability associated with the El Niño-Southern Oscillation (ENSO) leads to a decrease in mesoscale extremes during El Niño periods. Along the boundaries of the ETP OMZs transient shoaling events of the oxycline linked to ENSO dynamics or the seasonal cycle contribute to the generation of further pronounced low oxygen extreme events. The presented detection and tracking of low oxygen extremes is an important step towards a better understanding of extreme event occurrences and charac- teristics and lays the groundwork for further research such as the biogeochemical impact of such extremes.
X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. They are able to provide high resolution measurements in both space and time. Such features offer the opportunity to get accurate information not only about the targets' kinematics but also about the targets' extents. The tracking of these kinds of data is usually called extended target tracking (ETT).In this paper, we propose a signal processing chain mainly composed by a pixel-wise detector and a joint probabilistic data association tracker to handle the problem of multiple ETT. The performance assessment is conducted on real data acquired by an X-band marine radar located in the Gulf of La Spezia, Italy. The experimental results demonstrate that the processing chain is able to reach high performance with a limited computational burden.
This paper presents an overview of the functionalities of the Cognitive Communications Architecture (CCA) that is currently under development at the NATO Science and Technology Organisation (STO) Centre for Maritime Research and Experimentation (CMRE). The CCA is designed to enable the deployment of advanced autonomous underwater solutions making use of smart, adaptive and secure underwater networking strategies. The CCA and the implemented network modules have been extensively tested, validated and improved during various at-sea campaigns conducted in recent years, involving CMRE and partners. The collected results show that the CCA is a robust, reliable and effective solution supporting underwater communications and networking. It provides various functions and services for the development of novel cognitive and secure communication strategies, such as a cross-layer networking functionality and the ability to easily integrate various existing communications technologies. These aspects are key enablers in the construction of a system that is robust to challenging conditions, such as those posed by varying channel conditions or adversarial attacks.
Sidelobe interference artefacts are a common occurrence in multibeam echosounder water-column data. They are very commonly observed in the across-track dimension, where they appear as a semi-circular noise pattern, affecting in particular the data at a range beyond the minimum depth range. However, they also occur in the along-track dimension, where they affect data just above the seafloor near prominent features rising above the seabed. Here, we present a simple model for estimating the probable location of sidelobe interference artefacts in the along-track dimension. We test the accuracy of the model by comparing average energy levels at set distances from the seafloor both within and outside of the modeled location. We discuss how such models have the potential to identify the extent of useable water-column data acquired over complex bathymetry such as rocky reefs, so as to improve analysis of water-column data for the detection of near-benthic features, such as marine vegetation.
NOMAD is an autonomous benthic crawler carrying scientific instrumentation for scanning a continuous track of the seafloor and performing cyclic oxygen profiles and in-situ measurements of total exchange rates in depth of up to 6000m. It expands the line of preceding crawlers by achieving the highest payload to weight ratio by the application of function-integrating lightweight design that is instantiated as low-density design in the context of underwater systems.
In this work, we introduce a block sparse reconstruction technique to estimate backscattered echoes from underwater targets. The backscattered field of a spherical shell or the broadside scattering of a cylindrical shell contains a specular reflection as well as some elastic leaky surface waves, while the elastic parts appear as a periodic signal, which may be modeled using a block pattern. Thus, the parameters detailing the reflectors may be estimated using a convex optimization problem imposing the expected block structure. Numerical simulations and experiment results indicate the performance of the proposed method.
In the last decades the pollution of the oceans with plastic particles smaller than 5 mm, called microplastics has moved into the focus of science and governments. The analysis of particles especially <500 µm in size is a challenging field. These particles cannot be handled well manually and are therefore often concentrated on filters or meshes. By common FTIR microscopy the filter will be inspected visually and particles of interest marked for the following analysis. The manual selection process is prone to human bias, which can be overcome by FTIR imaging. Here, the complete filter area is mapped by FTIR using focal-plane-array (FPA) detectors, which collect several hundred spectra within one measurement for a large area. Each particle on the filter is therefore examined by FTIR spectroscopy. The results of this imaging can be either analyzed manually by the application of integrals for certain regions of the spectrum or automated. While the manual process is time consuming and prone to human bias we present an automated approach, which is totally impartial. With this process it is possible to analyze measurement files containing up to 1.8 million single spectra by library searches against an optimized database of different synthetic and natural polymers. The high quality data generated allowed image analysis, giving information for the particle size distribution for each polymer type as well as their distribution on the filter. All data was collected with relative ease even for complex sample matrices like (deep sea) sediments, waste water treatment plants, plankton samples and arctic ice cores. This approach has significantly decreased the expenditure of time for the interpretation of FTIR-imaging data and increased the quality of the generated data. The approach allows the standardization of microplastic analysis.
Microplastics (<5 mm) have become an increasing concern for the environment. These small plastic items can contain toxic ingredients and are assumed to accumulate persistent organic pollutants and heavy metals from the surroundings. Since microplastics are ingested by small organisms, they harbour the risk to propagate with these hazardous substances up the food chain. An environmental risk assessment is highly needed, but currently not possible since reliable data about the amount of microplastics in the environment are lacking. The detection of microplastics poses a challenge in many respects with the analytical investigation as one major issue. The most reliable techniques for the experienced analysis of microplastics are Raman and Fourier-Transform infrared (FTIR) spectroscopy. In this context, two highly promising approaches have been suggested to automate microplastics counting: chemical imaging and single-particle exploring (SPE). In this study, microplastics have been investigated for the first time by combined analysis with µ-Raman, ATR-FTIR, SPE coupled to µ-Raman (SPE-µ-Raman), and µ-FTIR chemical imaging in reflection-absorption mode
In this paper we consider the problem of autonomous landing on a horizontally moving platform with vertical unpredictable oscillatory dynamics using a quadrotor system. The quadrotor is equipped with an external Raspberry PI as a companion computer used for communications. The task is divided in two subproblems: tracking and landing. We present the algorithms involved for the entire procedure; a PI regulator is used for the tracking problem while descending is made by controlling relative vertical velocity. A finite state machine approach is chosen to manage multiple robot states and recover from failures. A software framework was developed in order to manage general flight missions and, in this case, the landing assignment. At the end, we performed simulation and real experiments in order to validate the outcome of this work.
Underwater acoustic (UA) channel is often affected by strong impulsive noise. In this paper, a compressive sensing based iterative algorithm is proposed to accurately estimate the channel state information and mitigate the impulsive noise, which is important to ensure high-speed data transmission in UA orthogonal frequency-division multiplexing communication systems. By exploiting the sparsity of the impulsive noise and channel impulse response in the time domain, we adopt the orthogonal matching pursuit algorithm to improve the accuracy of channel estimation with relatively low computational complexity. The proposed algorithm is evaluated through numerical simulations and real data collected during a UA communication experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that the proposed algorithm has a better performance than existing approaches.
A current trend is autonomous transport of goods and people in the air, at land, and at sea. For safe and reliable operations, autonomous systems require sensors that replace, or even exceed, the senses of a human operator. A system of spatially distributed inertial measurement units (IMUs) along the hull of a vessel, which allows sensing of local accelerations of a vessel or structure at sea is proposed. In contrast to classic motion sensors on ships, the sensors are not placed in a central location of the ship, but are instead mounted on the inside of hull of the vessel. This enables the system to measure local hull vibrations, which are induced by external forces or pressure gradients. The measurements can be processed to allow a spatial awareness of environmental loads or force fields acting on the vessel. After a discussion of the fundamentals of local motion sensing on a marine vessel, this paper presents two applications for distributed motion sensing. The first application is the measurement and classification of ice-induced vibrations in the hull of an Oden-class icebreaker during transit and stationkeeping in ice-infested waters. At four locations on the vessel, the local vibrations were measured and probability distribution function fitted to the motion data. It is shown, depending on the ice-conditions, that the stochastic properties of the signal change. In a second application, a model scale ship is equipped with an array of four motion sensors along the hull of the vessel and one virtual sensor in the center of gravity as a reference measurement. By this configuration, it is demonstrated how to detect local pressure zones along the hull caused by incoming waves.
This paper addresses the problem of compensating for motion-induced Doppler frequency offset in multicarrier acoustic communication systems based on orthogonal frequency division multiplexing (OFDM). In mobile acoustic systems, Doppler effect can be sever enough that the received OFDM signal experiences non-negligible frequency offsets even after initial resampling. To target these offsets, a practical method based on a hypothesis-testing approach is proposed. The method relies on differentially coherent detection which keeps the receiver complexity at a minimum and requires only a small pilot overhead. Differential encoding is applied across carriers, promoting the use of a large number of closely spaced carriers within a given bandwidth. This approach simultaneously supports frequency-domain coherence and efficient use of bandwidth for achieving high bit rates. While frequency synchronization capitalizes on differentially coherent detection framework, it can also be used as a pre-processing stage in coherent receivers without creating undue complexity. Using the experimental data transmitted over a 3-7 km shallow water channel in the 10.5-15.5 kHz acoustic band, we study the system performance in terms of data detection mean squared error (MSE) and bit error rate (BER), and show that the proposed method provides excellent performance at low computational cost.
