Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral information of deep-sea fished ecosystems is necessary to establish the sizes of marine protected areas within the framework of large international societal programs (e.g., European Community H2020, as part of the Blue Growth economic strategy). However, such information is currently scarce, and high-frequency and prolonged data collection is rarely available. Here, we report the implementation of autonomous underwater vehicles and remotely operated vehicles as an aid for acoustic long-baseline localization systems for autonomous tracking of Norway lobster (Nephrops norvegicus), one of the key living resources exploited in European waters. In combination with seafloor moored acoustic receivers, we detected and tracked the movements of 33 tagged lobsters at 400-m depth for more than 3 months. We also identified the best procedures to localize both the acoustic receivers and the tagged lobsters, based on algorithms designed for off-the-shelf acoustic tags identification. Autonomous mobile platforms that deliver data on animal behavior beyond traditional fixed platform capabilities represent an advance for prolonged, in situ monitoring of deep-sea benthic animal behavior at meter spatial scales.

Purpose: – This work aims to present the design of a new continuous tool-path strategy for open-source low-cost fused deposition modeling (FDM) machines, such as Fab@Home or RepRap; and the development of an innovative integrated tool to design and fabricate customized tracheal stents with any FDM machine and six patient parameters. Both contributions were validated and implemented by obtaining a customized medical-grade silicone tracheal stent. Design/methodology/approach: – For the design of the new deposition strategy, a Python programming language was used. The new tool-path strategy was proposed as a continuous path to avoid drops and gaps and to improve the accuracy of the final model. Meanwhile, patient parameters were obtained by medical doctors and introduced into the innovative integrated system. On the one hand, one mold generated automatically, and viewed with Matlab® software, was fabricated with a Fab@Home machine, optimized with the continuous tool-path strategy. On the other hand, the same generated mold was viewed in SolidWorks/Excel software and was fabricated using a commercial FDM machine. Finally, the mold was filled with medical grade silicone, and a silicone tracheal stent was obtained. Findings: – Path planning for extrusion technologies is still a major concern, especially for open-source FDM machines. The results obtained in this work show the benefits of applying the newly developed continuous tool-path strategy to optimize the performance and efficiency of these machines. In addition, the proposed innovative integrated system allows the fabrication of customized tracheal stents rapidly and affordably. Practical implications: – The possibility of obtaining customized tracheal stents is a worthy challenge. Medical doctors could play a more active role and interact during the design process, helping to obtain more suitable stents. The method proposed herein would provide the opportunity to obtain real values from the trachea of a patient in the operating room and quickly fabricate a customized stent that would fit the patient's trachea perfectly. Originality/value: – The results obtained in this work are relevant and have future applications in both the medical and the additive manufacturing fields. The optimized tool-path strategy can help to improve and enhance the use of low-cost FDM machines. Moreover, the innovative automatic design approach to fabricate tracheal stents may open new market opportunities in the medical device field.

We present a framework for planning collision-free paths online for autonomous underwater vehicles (AUVs) in unknown environments. It is composed of three main modules (mapping, planning and mission handler) that incrementally explore the environment while solving start-to-goal queries. We use an octree-based representation of the environment and we extend the optimal rapidly-exploring random tree (RRT*) using concepts of anytime algorithms and lazy collision evaluation, thus including the capability to replan paths according to nearby obstacles perceived during the execution of the mission. To validate our approach, we plan paths for the SPARUS-II AUV, a torpedo-shaped vehicle performing autonomous missions in a 2-dimensional workspace. We demonstrate its feasibility with the SPARUS-II AUV in both simulation and real-world in-water trials.

While commercially available autonomous underwater vehicles (AUVs) are routinely used in survey missions, a new set of applications exist which clearly demand intervention capabilities: the maintenance of permanent underwater structures as well as the recovery of benthic stations or black-boxes are a few of them. These tasks are addressed nowadays using manned submersibles or work-class remotely operated vehicles (ROVs), equipped with teleoperated arms under human supervision. In the context of the TRITON Spanish funded project, a subsea panel docking and an intervention procedure are proposed. The light-weight intervention AUV (I-AUV) Girona 500 is used to autonomously dock into a subsea panel using a funnel-based docking method for passive accommodation. Once docked, an autonomous fixed-based manipulation system, which uses feedback from a digital camera, is used to turn a valve and plug/unplug a connector. The paper presents the techniques used for the autonomous docking and manipulation as well as how the adapted subsea panel has been designed to facilitate such operations.