Integrated manufacturing of REciclable multi-material COmposites for the TRANSport sector

en de,en,es,fr,it,pl 449189 449189-new-algorithms-enable-the-use-of-adaptive-autonomous-underwater-vehicles New algorithms enable the use of adaptive autonomous underwater vehicles With a focus on reinforcement learning algorithms, researchers are advancing the use of adaptive autonomous underwater vehicles for marine animal tracking. Earth’s underwater ecosystems are under threat, the result of climate change, pollution and overuse, among other environmental factors. “One of our common European goals is to protect the health and biodiversity of marine environments,” says https://sites.google.com/view/ivanmasmitja/home (Ivan Masmitja), a researcher at the https://www.icm.csic.es/en (Institut de Ciències del Mar) (ICM-CSIC). “However, protecting and conserving these extremely important ecosystems requires completely new, groundbreaking approaches.” One such approach is the use of adaptive autonomous underwater vehicles (AUVs), essentially underwater drones. According to Masmitja, AUVs have the potential to enable researchers to get an unparalleled look at our marine environments and collect data on a wide range of environmental factors. “The challenge is that it is very difficult to localise and track underwater objects, especially marine life,” he explains.With the support of the EU-funded https://sites.google.com/view/aiforutracking (AIforUTracking) project, researchers at ICM-CSIC look to help solve this problem by using machine learning-based algorithms. “Moving towards the envisioned applications of marine animal tracking by autonomous vehicles, this project is at the forefront of research and directly advances the objectives outlined by the EU’s https://bit.ly/3SlyluL (Marine Strategy Framework Directive),” adds https://www.icm.csic.es/en/staff/joan-navarro-bernabe-2167 (Joan Navarro), also a researcher at ICM-CSIC who participated in this project.This research was undertaken with the support of the https://marie-sklodowska-curie-actions.ec.europa.eu/ (Marie Sk?odowska-Curie Actions) programme.<br /> <b>Reinforcement learning to track underwater targets</b><br /> At the heart of the project is the use of reinforcement learning (RL). “RL is a unique corner of machine learning that aims to optimise control by looking at how an intelligent agent should act within a dynamic environment in order to achieve the desired result,” remarks Navarro.Within the framework of the project, that means using RL to help the AUV find the optimal path to track underwater targets using range-only information. But as is the case with many research projects, doing so was easier said than done.“One of the main challenges we faced was incorporating the RL algorithms into existing AUVs, many of which lacked a CPU strong enough to handle the necessary software packages,” notes Masmitja. “Instead, we had to write the RL network from scratch using basic mathematical notations.”<br /> <b>Machine learning helps with target localisation</b><br /> With the RL written and installed, it was time to put the AIforUTracking solution to the test. For that, the project team headed to California. Placing an RL-enabled AUV into Monterey Bay, researchers successfully tracked the drone from a surface vehicle for several hours and for more than 2.5 kilometres.“For the first time ever, we demonstrated that RL algorithms can be trained and used to tackle major issues in underwater missions such as target localisation,” says Navarro.<br /> <b>Using algorithms to coordinate a fleet of underwater autonomous vehicles</b><br /> In addition to RL, the project also worked with multi-agent reinforcement learning (MARL) algorithms. Specifically, researchers developed a new algorithm with transformers that outperformed state-of-the-art algorithms in different scenarios. Masmitja says that this represents another major milestone as MARL could be used to coordinate a fleet of vehicles to explore the ocean. “With the techniques we developed and implemented, we are making big steps toward more autonomous and adaptable vehicles for exploring, studying and monitoring the ocean and the many creatures that call it home,” he concludes. Many of the project’s results have been published in https://www.science.org/doi/10.1126/scirobotics.ade7811 (‘Science Robotics’), one of the most prestigious journals in the robotics sector.<br /> AIforUTracking, biodiversity, marine environment, algorithms, autonomous underwater vehicles, marine animal tracking, climate change, drones 2024-02-09 15:06:47 2024-02-09 15:06:44 2024-02-09 15:06:48 en de,en,es,fr,it,pl env Climate Change and Environment /Climate Change and Environment en de,en,es,fr,it,pl brief Result in Brief Article: Classic and enhanced /Result in Brief en de,en,es,fr,it,pl editorial CORDIS Editorial Written by CORDIS /CORDIS Editorial es 3763515 edit-klensni en 227912 893089 AIforUTracking The Artificial Intelligence methods for Underwater target Tracking (AIforUTracking) project will bring to the scientific community new tools for underwater target tracking by Autonomous Underwater Vehicles (AUVs) using Reinforcement Learning (RL) techniques. Moving towards the... Artificial Intelligence methods for Underwater target Tracking en de,en,es,fr,it,pl project Project Project factsheets /Project en de,en,es,fr,it,pl /1731 autonomous vehicles /engineering and technology/mechanical engineering/vehicle engineering/automotive engineering/autonomous vehicles en de,en,es,fr,it,pl /525 behavioural psychology /social sciences/psychology/behavioural psychology en de,en,es,fr,it,pl /1587 reinforcement learning /natural sciences/computer and information sciences/artificial intelligence/machine learning/reinforcement learning en en MSCA-IF Marie Sk?odowska-Curie Individual Fellowships (IF) Marie Sk?odowska-Curie Individual Fellowships (IF) /Marie Sk?odowska-Curie Individual Fellowships (IF) en de,en,es,fr,it,pl corda CORDA RTD research data warehouse /CORDA en 704413 MSCA-IF-2019 H2020 Individual Fellowships 20200 H2020-Topics en topic Topic Programme: Part of the Commission work programme implementing legal basis /Topic en corda CORDA RTD research data warehouse /CORDA de,en,es,fr,it,pl 664109 H2020-EU.1.3. H2020 H2020-EU.1.3. EXCELLENT SCIENCE - Marie Sk?odowska-Curie Actions Marie-Sklodowska-Curie Actions 664091 H2020-EU.1. 664087 H2020-EC 664086 H2020 en legalbasis Legal Basis Programme: Legal basis for research funding /Legal Basis en editorial CORDIS Editorial Written by CORDIS /CORDIS Editorial de,en,es,fr,it,pl 664113 H2020-EU.1.3.2. H2020 H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility MSCA Mobility 664109 H2020-EU.1.3. 664091 H2020-EU.1. 664087 H2020-EC 664086 H2020 en legalbasis Legal Basis Programme: Legal basis for research funding /Legal Basis en editorial CORDIS Editorial Written by CORDIS /CORDIS Editorial en en,de,es,fr,it,pl,any /docs/article/images/2024-01/449189.jpg image/jpeg 62728 © Jesper/stock.adobe.com 0cffab989a35e3bf24042d8a8575048638697b0c5f2b426db8a3c5e2b40a6f15 Spain 242387496 ES ES ES article

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