Publications
Introducing Guard Frames to Ensure Schedulability of All TSN Traffic Classes
Offline scheduling of Scheduled Traffic (ST) in Time-Sensitive Networks (TSN) without taking into account the quality of service of non-ST traffic, e.g., time-sensitive traffic such as Audio-Video Bridging (AVB) traffic, can potentially cause deadline misses for...
Opportunities and Specific Plans for Migrating from PRP to TSN in Substation Automation Systems
Electrical substations are vital for the power grid, and Substation Automation Systems (SASs) have been employed to enhance substation functionality and safety. As the energy landscape evolves, substations face new challenges such as accommodating an increasing...
Evolving Real-time Stereo Odometry for AUV Navigation in Challenging Marine Environments
Assessing benthic marine habitats colonised with posidonia oceanica using autonomous marine robots and deep learning: A eurofleets campaign
Data-driven Exploration of Benthic Environments with Autonomous Underwater Vehicles Featuring Semantic Perception and Adaptive Navigation Intelligence
Most of the land terrain on Earth is being constantly mapped using sub-meter resolution spaceborne images. However, about eighty percent of the oceans’ seafloor remains unexplored and most of the benthic habitat and geological structure distribution continues unknown....
Efficient Implementation of Deep Nets for Video Processing to Preserve Marine Ecosystem Services
Marine ecosystems provide multiple services to humans, including provisioning services, such as seafood or fossil energy; regulating services, like coastal protection or water purification; cultural services, as tourism or spiritual benefits; and supporting services,...
Mesopelagic Crustacean Habitat Identification and Analysis Using Deep Learning
Towards Hash Similarity and Geometric-based Image Filtering to Lighten Underwater Photo-Mosaicing
Using Deep Neural Networks to Detect and Track Fish in Underwater Video Sequences
A crucial task in marine research is that of monitoring fish in order to quantify different species and analyze their behavior. Computer Vision clearly helps in solving this problem, especially when combined with Deep Learning. This paper focuses on the use of Deep...
Towards Underwater Robust Image Transmission Using Acoustic Communications
Real-time image exchange among different marine autonomous robots can be a requirement in some applications, and it becomes a real challenge particularly in underwater systems with restricted bandwidth communications. Some examples where visual data transmission is...
Image Compression for Underwater Multi-Robot Loop Closing
Development and Testing of a Navigation Solution for Autonomous Underwater Vehicles based on Stereo Vision
Complete list of authors: Simone Tani (corresponding author), Francesco Ruscio, Matteo Bresciani, Bo Miquel Nordfeldt, Francisco Bonin-Font, Riccardo Costanzi, Francesco Ruscio, Matteo Bresciani, and Riccardo Costanzi : Dipartimento di Ingegneria dell’Informazione,...
Hierarchical Color Encoding for Progressive Image Transmission in Underwater Environments
This letter presents the Progressive Hierarchical Image Encoding (PHIE) approach aimed at progressively encoding underwater images and, thus, helping in transmitting them in unreliable, low bandwidth, subaquatic communication channels. The proposal splits an image...
Exploring the use of Deep Reinforcement Learning to allocate tasks in Critical Adaptive Distributed Embedded Systems
A Critical Adaptive Distributed Embedded System (CADES) is a group of interconnected nodes that must carry out a set of tasks to achieve a common goal, while fulfilling several requirements associated to their critical (e.g. hard real-time requirements) and adaptive...
Xiroi II, an Evolved ASV Platform for Marine Multirobot Operations
In this paper, we present the design, development and a practical use of an Autonomous Surface Vehicle (ASV) as a modular and flexible platform for a large variety of marine tasks including the coordination strategies with other marine robots. This work tackles the...
Speeding Task Allocation Search for Reconfigurations in Adaptive Distributed Embedded Systems Using Deep Reinforcement Learning
A Critical Adaptive Distributed Embedded System (CADES) is a group of interconnected nodes that must carry out a set of tasks to achieve a common goal, while fulfilling several requirements associated with their critical (e.g., hard real-time requirements) and...
Real-Time Pipe and Valve Characterisation and Mapping for Autonomous Underwater Intervention Tasks
Nowadays, more frequently, it is necessary to perform underwater operations such as surveying an area or inspecting and intervening on industrial infrastructures such as offshore oil and gas rigs or pipeline networks. Recently, the use of Autonomous Underwater...
Progressive Hierarchical Encoding for Image Transmission in Underwater Environments
This paper proposes a method to progressively encode underwater images. The image information is split into several, very small, parts called chunks that can be easily transmitted using unreliable, low bandwidth, underwater communication channels. The receiver can...
A Loop Selection Front-end for Underwater Visual GraphSLAM
This paper presents an algorithm to reject false loops ready to be used as a front-end for GraphSLAM. The proposal operates in two steps. The first one checks each loop independently to reduce the computational cost of the second one, which jointly checks the...
Implementación y verificación de mecanismos para tolerar fallos en el canal de comunicaciones de manera dinámica en sistemas distribuidos empotrados de tiempo real críticos basados en Ethernet
Desde el 1980 están apareciendo soluciones tecnológicas que han ido acercando a las redes de ordenadores al concepto de sistemas distribuidos. Desde los 80 que aparecen los primeros sistemas operativos distribuidos, así como las redes LAN, hasta a hoy en día, que una...