Results 161 to 170 of about 3,433 (259)

Domain knowledge embedded anti-disturbance autonomous navigation for marine vehicles. [PDF]

Commun Eng
Zhao Y, Ma Y, Zhu G, Hu S, Wang W, Yan X.   +5 more
europepmc   +1 more source

Deep Reinforcement Learning for Autonomous Underwater Navigation: A Comparative Study with DWA and Digital Twin Validation. [PDF]

Sensors (Basel)
Mari Z, Nawaf MM, Drap P.
europepmc   +1 more source

Remote Sensing With Machine Learning to Monitor Seagrass Meadows: Long‐Term Trends in Tauranga Harbour, New Zealand

New Zealand Journal of Marine and Freshwater Research, Volume 60, Issue 3, September 2026.
Seagrass meadows play critical roles in coastal ecosystems by stabilising sediments, supporting biodiversity and sequestering carbon, yet monitoring their recovery at scale is often constrained by the lack of scalable and repeatable approaches. This study applies an open‐source remote‐sensing framework to track long‐term changes in Zostera muelleri in ...
Zhanchao Shao, Karin R. Bryan, Sanne M. Vaassen, Conrad A. Pilditch, Brooke Ellis‐Smith, Josie A. Crawshaw   +5 more
wiley   +1 more source

Design and implementation of a biomimetic turtle hydrofoil for an autonomous underwater vehicle. [PDF]

Sensors (Basel), 2011
Font D, Tresanchez M, Siegentahler C, Pallejà T, Teixidó M, Pradalier C, Palacin J.   +6 more
europepmc   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, Volume 43, Issue 6, Page 3617-3632, September 2026.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source

Research on Underwater Scene Reconstruction for Mobile Platforms Based on Rotating Scanning Sonar. [PDF]

Sensors (Basel)
Tan L, Wang L, Chen C.
europepmc   +1 more source

Actuation Strategies for Underwater Jet‐Propelled Soft Robots

Journal of Field Robotics, Volume 43, Issue 6, Page 3868-3892, September 2026.
ABSTRACT This review article examines jet‐propulsion mechanisms in underwater soft robotic systems, focusing exclusively on physically fabricated and experimentally validated robots. Covering research published from 2013 to 2025, this study classifies and evaluates jet‐propulsion robots based on their actuation mechanisms.
Angel Kitone, Mohammed Anteet, Pawandeep S. Matharu, Yara Almubarak   +3 more
wiley   +1 more source

Exploring the Use and Impact of Composite Materials in Robotics: A Systematic Review

Journal of Field Robotics, Volume 43, Issue 6, Page 4037-4060, September 2026.
ABSTRACT Lightweight and high‐strength materials are important in robotics, as structural design impacts efficiency, payload capacity, and energy consumption. Composite materials, with their superior stiffness‐to‐weight ratios and multifunctional properties, offer clear advantages over conventional metals and polymers.
Doglas Negri, Gabriela Wessling Oening, Felipe Augusto Carvalho de Faria, Sarah Maria Schroeder, Ricardo De Medeiros   +4 more
wiley   +1 more source

Bionic Tactile Skins for Robotics: Fundamentals, Advances, and Future Prospects

SmartSys, Volume 2, Issue 3, September 2026.
ABSTRACT Robotic bionic tactile skins (RBTSs), as crucial components of next‐generation robotic systems, have attracted significant attention in recent years. By enabling robots to achieve human‐like tactile perception and interact effectively with their surroundings, RBTSs play an essential role in enhancing robotic intelligence.
Jiajun Wu, Zitong Zhang, Xuhui Zhou, Yu Meng, Jie Ni, Junshan Liu, Faheng Zang, Xiaojun Guo, Zhuoqing Yang   +8 more
wiley   +1 more source

HydroAir: An Air-Propelled Surface Vehicle for Autonomous Navigation and 3D Reconstruction in Shallow and Obstacle-Rich Aquatic Environments. [PDF]

Sensors (Basel)
Honório LM, Vidal VF, Biundini IZ, Machado RA, Fernandes F, Santos MFD.   +5 more
europepmc   +1 more source