Underwater Environment
Underwater environment research focuses on developing robust and efficient methods for exploration, mapping, and object manipulation in challenging aquatic settings. Current efforts concentrate on improving autonomous underwater vehicle (AUV) navigation and perception using advanced computer vision techniques (e.g., convolutional neural networks, transformers, and deep unfolding networks), acoustic sensing, and innovative robotic designs (e.g., biomimetic robots, soft robots). These advancements are crucial for various applications, including search and rescue, environmental monitoring, and infrastructure inspection, ultimately enhancing our understanding and interaction with the underwater world.
Papers
Towards Optimal Human-Robot Interface Design Applied to Underwater Robotics Teleoperation
Paulo Padrao, Jose Fuentes, Tero Kaarlela, Alfredo Bayuelo, Leonardo Bobadilla
FisHook -- An Optimized Approach to Marine Specie Classification using MobileNetV2
Kohav Dey, Krishna Bajaj, K S Ramalakshmi, Samuel Thomas, Sriram Radhakrishna
Online Stochastic Variational Gaussian Process Mapping for Large-Scale SLAM in Real Time
Ignacio Torroba, Marco Chella, Aldo Teran, Niklas Rolleberg, John Folkesson
Learning Visual Representation of Underwater Acoustic Imagery Using Transformer-Based Style Transfer Method
Xiaoteng Zhou, Changli Yu, Shihao Yuan, Xin Yuan, Hangchi Yu, Citong Luo