António Bernardo Ferreira

Abstract
Highlights: What are the main findings? The SLAM method, based on the registration of 3D profiling sonar scans using the 3DupIC method, avoids the construction of submaps and thereby overcomes the limitations of other state-of-the-art approaches. Simultaneous optimization of the trajectory and extrinsic parameters, using the proposed SLAM and calibration method, ensures high accuracy in trajectory and map estimation. What is the implication of the main finding? Direct registration of raw scans supports two distinct applications. On the one hand, it enables pose estimation through odometry. On the other hand, it provides loop-closure constraints for the SLAM process. 3D profiling sonars are highly effective sensors for mapping, localization, and SLAM applications. This demonstration is particularly important as newer, smaller, and more affordable sonars in this category become available, contributing to their wider adoption. High resolution underwater mapping is fundamental to the sustainable development of the blue economy, supporting offshore energy expansion, marine habitat protection, and the monitoring of both living and non-living resources. This work presents a pose-graph SLAM and calibration framework specifically designed for 3D profiling sonars, such as the Coda Octopus Echoscope 3D. The system integrates a probabilistic scan matching method (3DupIC) for direct registration of 3D sonar scans, enabling accurate trajectory and map estimation even under degraded dead reckoning conditions. Unlike other bathymetric SLAM methods that rely on submaps and assume short-term localization accuracy, the proposed approach performs direct scan-to-scan registration, removing this dependency. The factor graph is extended to represent the sonar extrinsic parameters, allowing the sonar-to-body transformation to be refined jointly with trajectory optimization. Experimental validation on a challenging real world dataset demonstrates outstanding localization and mapping performance. The use of refined extrinsic parameters further improves both accuracy and map consistency, confirming the effectiveness of the proposed joint SLAM and calibration approach for robust and consistent underwater mapping. © 2026 by the authors.

Abstract
Due to space and energy restrictions, lightweight autonomous underwater vehicles (AUVs) are usually fitted with low-power processing units, which limits the ability to run demanding applications in real time during the mission. However, several robotic perception tasks reveal a parallel nature, where the same processing routine is applied for multiple independent inputs. In such cases, leveraging parallel execution by offloading tasks to a GPU can greatly enhance processing speed. This article presents a collection of generic matrix manipulation kernels, which can be combined to develop parallelized perception applications. Taking advantage of those building blocks, we report a parallel implementation for the 3DupIC algorithm-a probabilistic scan matching method for sonar scan registration. Tests demonstrate the algorithm's real-time performance, enabling 3D sonar scan matching to be executed in real time onboard the EVA AUV.

Abstract
This paper presents the results of field trials performed with the EVA autonomous underwater vehicle in the protection of critical infrastructures. The trials were conducted in the context of the REPMUS23 naval exercise organized by the Portuguese Navy. EVA was successfully deployed in a mission of detailed inspection of a submarine cable and in the detection and localization of a possible hostile attack with explosive charges. Multibeam sonar and structured laser light systems were also used to locate and obtain a detailed model of the TURTLE robotic lander deployed on the sea bottom.

Abstract
This paper underscores the critical role of evolving tools for underwater search and rescue. Successful submarine crew rescue hinges on detecting, locating, and obtaining detailed information about the submerged vessel. Robotic systems, particularly ROVs and AUVs, emerge as invaluable tools, offering swift deployment times compared to manned submersibles. This study presents findings from Submarine Escape and Rescue (SMER) field trials conducted during the REPMUS 2023 naval military exercise off the west coast of Portugal, showcasing the effectiveness of these tools in real-world emergency situations. An initial multibeam sonar search from the surface with the Mar Porfundo ship was performed, followed by a close detailed inspection and visual survey with the EVA AUV of a target military submarine (NRP Arp (a) over tildeo) stationed on the sea bottom.

Abstract
This paper addresses the problem of high-bandwidth communication and data recovery from deep-sea semi-permanent robotic landers. These vehicles are suitable for long-term monitoring of underwater activities and to support the operation of other robotic assets in Operation & Maintenance (O&M) of offshore renewables. Limitations of current communication solutions underwater deny the immediate transmission of the collected data to the surface, which is alternatively stored locally inside each lander. Therefore, data recovery often implies the interruption of the designated tasks so that the vehicle can return to the surface and transmit the collected data. Resorting to a short-range and high-bandwidth optical link, an alternative underwater strategy for flexible data exchange is presented. It involves the usage of an AUV satellite approaching each underwater node until an optical communication channel is established. At this point, high-bandwidth communication with the remote lander becomes available, offering the possibility to perform a variety of operations, including the download of previously recorded information, the visualisation of video streams from the lander on-board cameras, or even performing remote motion control of the lander. All these three operations were tested and validated with the experimental setup reported here. The experiments were performed in the Atlantic Ocean, at Setubal underwater canyon, reaching the operation depth of 350m meters. Two autonomous robotic platforms were used in the experiments, namely the TURTLE3 lander and the EVA Hybrid Autonomous Underwater Vehicle. Since EVA kept a tether fibre optic connection to the Mar Profundo support vessel, it was possible to establish a full communication chain between a landbased control centre and the remote underwater nodes.