arXiv:2607. 28306v1 Announce Type: cross Abstract: Recent incidents of accidental damage and suspected sabotage to submarine telecommunication and power cables, particularly in the Baltic Sea, have underscored their vulnerability and the need for continuous monitoring solutions.
By Erick Eduardo Ramirez-Torres, Javier Macias-Guarasa, Daniel Pizarro, Javier Tejedor, Sira Elena Palazuelos-Cagigas, Pedro J. Vidal-Moreno, Mar\'ia R. Fern\'andez-Ruiz, Sonia Martin-Lopez, Miguel Gonzalez-Herraez, Roel Vanthillo
arXiv:2607. 11686v1 Announce Type: cross Abstract: Low-cost unmanned ground vehicles are often used in indoor places like warehouses, inspection corridors, and farm rows, where painted floor lines guide the robot.
By Jakob Solberg Berntzen, Safia Fatima, Leon Moonen
arXiv:2609.22353v1 Announce Type: new
Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained p...
By Savio Cardoz, Santhiya Rajan
arXiv:2607. 04906v1 Announce Type: new Abstract: Under the Shipping 4.
By Ming-Kuan Lin, Yi-Chung Lai, Ming-Hsin Chiang, Tsung-Wei Pan, Jung-Hua Wang
arXiv:2607. 18013v1 Announce Type: cross Abstract: This paper introduces a method for real-time processing and transmission of autonomous underwater vehicle (AUV) imagery over low-bandwidth communication links.
By Adrian Bodenmann, Cailei Liang, Miquel Massot-Campos, Samuel Simmons, Alexander B. Phillips, Alberto Consensi, Matthew Kingsland, Rashiid Sherif, Stan Brown, Adam Riese, Blair Thornton
AquaBEV is a monocular underwater occupancy model that predicts local bird’s‑eye‑view (BEV) occupancy from a single RGB image. It uses paired 3D imaging sonar data as geometric supervision during training, mapping visual features into a calibration‑free polar representation and decoding along the range dimension before reconstructing Cartesian BEV coordinates. In a controlled underwater occupancy benchmark, AquaBEV outperforms the strongest transferred baseline with 31.4 % Visible IoU and 38.6 % Observed IoU, achieving 4.0 % and 4.3 % relative improvements respectively.
By Trung Tien Dong, Shengji Jin, Chen Chen, Yi Sheng, Xiaomin Lin