The EUMarineRobots (EUMR) project is glad to announce the third “Coffee with EUMR” webinar on Friday, 12 March 2021 at 14:30 CET. This webinar will be hosted by the AIR Centre and will consist of two short talks invited by the coordinator University of Porto in collaboration with the Swedish Maritime Robotics Centre (SMaRC). The first talk is titled “Neural representations and generative models for sonar data”, which will be given by Dr. Nils Bore, from the Swedish Maritime Robotics Centre (SMaRC), KTH Royal Institute of Technology, Stockholm. In the second talk, Miguel Aguiar, also from the KTH Royal Institute of Technology, will talk about "Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models".
Please use this link to join the meeting.
The abstracts of the talks and short speakers' biographies follow:
Abstract "Neural representations and generative models for sonar data"
Physical modeling of sonar is complex, and often infeasible without detailed data on the modeled subsea environment. Simulation methods therefore tend to simplify sonar modeling in the interest of practical simulations. Fusion of sonar data into high-definition models face similar obstacles. In particular, sonars with wide beam angles require significant simplifications in order to construct bathymetry or object models. We present a line of research that replaces classical sonar models by black box neural networks. By relying on learnt models rather than hand-crafted ones, we hope to enhance the model quality by supplying more data, rather than manually fine-tuning for each environment or object. This has the potential of greatly enhancing statistical and visual fidelity. We investigate neural representation learning as well as generative adversarial models (GANs) as representations of sonar data. We showcase applications of each method to sidescan simulation and to bathymetry reconstruction from sidescan. Both GANs and neural representations have contributed to significant advances in visual sensing, and our preliminary results demonstrate their practicality in the subsea domain.
Nils Bore received the M.Sc. degree in mathematical engineering from the Faculty of Engineering, Lund University, Lund, Sweden, in 2012, and the Ph.D. degree in computer vision and robotics from the Robotics Perception and Learning Lab, Royal Institute of Technology (KTH), Stockholm, Sweden, in 2018. He is currently a researcher with the Swedish Maritime Robotics (SMaRC) project at KTH. His research interests include robotic sensing and mapping, with a focus on probabilistic reasoning and inference. Most of his recent work has been on applications of specialized neural networks to underwater sonar data. In addition, he is interested in system integration for robust and long-term robotic deployments.
Abstract "Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models"
AUVs have been successfully used as mobile sensors in oceanographic applications for over a decade. However, marine vehicles typically have relatively low speed and endurance, making it interesting to use the energy in the currents to simultaneously reduce commuting times and power consumption. This is particularly true in coastal operations with small portable AUVs, where the magnitude of the water velocity can exceed the vehicles' maximum speed. In this talk a method for AUV trajectory optimization based on dynamic programming and high resolution model forecasts of the water velocity will be presented, as well as its implementation. The discussion will be illustrated by numerical simulations and experimental results in the Sado estuary in Portugal.
Miguel Aguiar is currently a doctoral student at the Division of Decision and Control Systems, KTH Royal Institute of Technology in Stockholm, Sweden.
Previously he was a research engineer at LSTS at the University of Porto, where he did research on trajectory optimization for marine vehicles and developed control and guidance software for AUVs. He obtained an MSc in Electrical and Computers Engineering from the University of Porto in 2019 with a dissertation on trajectory optimization for marine vehicles.