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
Scalable Semantic 3D Mapping of Coral Reefs with Deep Learning
Jonathan Sauder, Guilhem Banc-Prandi, Anders Meibom, Devis Tuia
UWA360CAM: A 360$^{\circ}$ 24/7 Real-Time Streaming Camera System for Underwater Applications
Quan-Dung Pham, Yipeng Zhu, Tan-Sang Ha, K. H. Long Nguyen, Binh-Son Hua, Sai-Kit Yeung
UIVNAV: Underwater Information-driven Vision-based Navigation via Imitation Learning
Xiaomin Lin, Nare Karapetyan, Kaustubh Joshi, Tianchen Liu, Nikhil Chopra, Miao Yu, Pratap Tokekar, Yiannis Aloimonos
Enhancing scientific exploration of the deep sea through shared autonomy in remote manipulation
Amy Phung, Gideon Billings, Andrea F. Daniele, Matthew R. Walter, Richard Camilli
Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions
Muhayyuddin Ahmed, Ahsan Baidar Bakht, Taimur Hassan, Waseem Akram, Ahmed Humais, Lakmal Seneviratne, Shaoming He, Defu Lin, Irfan Hussain
ChatSim: Underwater Simulation with Natural Language Prompting
Aadi Palnitkar, Rashmi Kapu, Xiaomin Lin, Cheng Liu, Nare Karapetyan, Yiannis Aloimonos