Abstract
Some structures in the harbour environment need to be inspected regularly. However, these scenarios present a major challenge for the accurate estimation of a vehicle's position and subsequent recognition of similar images. In these scenarios, visibility can be poor, making place recognition a difficult task as the visual appearance of a local feature can be compromised. Under these operating conditions, imaging sonars are a promising solution. The quality of the captured images is affected by some factors but they do not suffer from haze, which is an advantage. Therefore, a purely acoustic approach for unsupervised recognition of similar images based on forward-looking sonar (FLS) data is proposed to solve the perception problems in harbour facilities. To simplify the variation of environment parameters and sensor configurations, and given the need for online data for these applications, a harbour scenario was recreated using the Stonefish simulator. Therefore, experiments were conducted with preconfigured user trajectories to simulate inspections in the vicinity of structures. The place recognition approach performs better than the results obtained from optical images. The proposed method provides a good compromise in terms of distinctiveness, achieving 87.5% recall considering appropriate constraints and assumptions for this task given its impact on navigation success. That is, it is based on a similarity threshold of 0.3 and 12 consistent features to consider only effective loops. The behaviour of FLS is the same regardless of the environment conditions and thus this work opens new horizons for the use of these sensors as a great aid for underwater perception, namely, to avoid degradation of navigation performance in muddy conditions.

Abstract
Gamma radiation over the Atlantic Ocean was measured continuously from January to May 2020 by a NaI(Tl) detector installed on board the Portuguese navy's ship NRP Sagres. Enhancements in the gamma radiation values are identified automatically by an algorithm for detection of anomalies in mean and variance as well as by visual inspection. The anomalies are typically +50% above the background level and relatively rare events (similar to<10% of the days). All the detected anomalies are associated with simultaneous precipitation events, consistent with the wet deposition of scavenged radionuclides. The enhancements are detected in the open ocean even at large distances (+500 km) from the nearest coastline. Back trajectories reveal that half of these events are associated with air masses experiencing continental land influences, but the other half do not display evidence of recent land contact. The enhancements in gamma radiation very far from land and with no evidence of continental fetch from back trajectories are difficult to explain as resulting only from radionuclides with a terrestrial source such as radon and its progeny. Further investigation and additional measurements are needed to improve understanding on the sources of ambient radioactivity in the open ocean and assess whether gamma radiation in the marine environment is influenced not only by radionuclides of terrestrial origin, but also cosmogenic radionuclides, like Beryllium-7, formed in the upper atmosphere but with the ability to be transported downward and serve as a tracer of the aerosols to which it attaches. Plain Language Summary Radioactive elements such as the noble gas radon and those produced by its radioactive decay are naturally present in the environment and used as tracers of atmospheric transport and composition. In particular, the noble gas radon, being inert and of predominantly terrestrial origin, is used to identify pristine marine air masses with no land contamination. Precipitation over land typically brings radon from the atmosphere to the surface, enhancing gamma radiation on the ground, but such enhancements have not been identified before nor expected over the ocean due to the low amount of radon typical of marine air masses. Here we report, for the first time, gamma radiation enhancements associated with precipitation in the oceanic environment, using measurements performed over the Atlantic Ocean in a campaign onboard the Portuguese navy ship NRP Sagres.

Abstract
This work addresses reconstructing an ancient mining site in three-dimensional (3D) modelling with robotic systems, processing the information from two visible spectrum cameras. The developed solution, GeoTec System, was validated in an underground environment in the Monastery of Tibães (Braga, NW Portugal). This study was developed under the MineHeritage project's scope, aiming to attain society on the importance of raw materials across a historical approach. The outputs acquired from the datasets developed in a successful 3D reconstruction of the main gallery and secondary tunnels of the Aveleiras mine in Tibães. However, the investigation is still ongoing to contribute to applying 3D reconstruction technologies, GIS-based mapping and geovisualization techniques in the underground heritage environment.

Abstract
The use of autonomous vehicles in maritime operations is a technological challenge. In the particular case of autonomous aerial vehicles (UAVs), their application ranges from inspection and surveillance of offshore power plants, and marine life observation, to search and rescue missions. Manually landing UAVs onboard water vessels can be very challenging due to limited space onboard and wave agitation. This paper proposes an autonomous solution for the task of landing commercial multicopter UAVs with onboard cameras on water vessels, based on the detection of a custom landing platform with computer vision techniques. The autonomous landing behavior was tested in real conditions, using a research vessel at sea, where the UAV was able to detect, locate, and safely land on top of the developed landing platform.

Abstract
This paper presents the TURTLE hybrid robotic lander in the context of the field trials performed in the REP(MUS) 2022 military exercise. The TURTLE robot combines the characteristics and mobility of an autonomous underwater vehicle with the ones of a seabed lander, having been designed for extended permanence on the sea bottom and efficient ascending and dive to the deep sea. The REP( MUS) 2022 exercises organized by the Portuguese navy in collaboration with NATO organizations and other institutions demonstrated the large-scale use of unmanned marine systems in an operational scenario. The robotic system is presented as well as some of the results and experience from the field trials.

Abstract
By creating a dependable, transparent, and cost-effective system for forecasting and ongoing environmental impact monitoring of exploration and exploitation activities in the deep sea, TRIDENT seeks to contribute to the sustainable exploitation of seabed mineral resources. In order to operate autonomously in remote locations under harsh conditions and send real-time data to authorities in charge of granting licenses and providing oversight, this system will create and integrate new technology and innovative solutions. The efficient monitoring and inspection system that will be created will abide by national and international legal frameworks. At the sea surface, mid-water, and the bottom, TRIDENT will identify all pertinent physical, chemical, geological, and biological characteristics that must be monitored. It will also look for data gaps and suggest procedures for addressing them. These are crucial actions to take in order to produce accurate indicators of excellent environmental status, statistically robust environmental baselines, and thresholds for significant impact, allowing for the standardization of methods and tools. In order to monitor environmental parameters on mining and reference areas at representative spatial and temporal scales, the project consortium will thereafter develop and test an integrated system of stationary and mobile observatory platforms outfitted with the most recent automatic sensors and samplers. The system will incorporate high-capacity data processing pipelines able to gather, transmit, process, and display monitoring data in close to real-time to facilitate prompt actions for preventing major harm to the environment. Last but not least, it will offer systemic and technological solutions for predicting probable impacts of applying the developed monitoring and mitigation techniques.