Autonomous driving on water surfaces plays an essential role in executing hazardous and
time-consuming missions, such as maritime surveillance, survivor rescue, environmental …

Radar has stronger adaptability in adverse scenarios for autonomous driving environmental
perception compared to widely adopted cameras and LiDARs. Compared with commonly …

Water segmentation is essential for the autonomous driving system of unmanned surface
vehicles (USVs), which provides reliable navigation for making safety decisions. However …

Current perception models for different tasks usually exist in modular forms on Unmanned
Surface Vehicles (USVs), which infer extremely slowly in parallel on edge devices, causing …

With the rapid advancements of sensor technology and deep learning, autonomous driving
systems are providing safe and efficient access to intelligent vehicles as well as intelligent …

Sensor fusion is crucial for an accurate and robust perception system on autonomous
vehicles. Most existing datasets and perception solutions focus on fusing cameras and …

Urban water-surface robust perception serves as the foundation for intelligent monitoring of
aquatic environments and the autonomous navigation and operation of unmanned vessels …

A reliable obstacle detection system is crucial for autonomous surface vehicles (ASVs) to
realize fully autonomous navigation with no need of human intervention. However, the …

In recent years, unmanned surface vehicles (USVs) have been experiencing growth in
various applications. With the expansion of USVs' application scenes from the typical marine …

With the development of Unmanned Surface Vehicles (USVs), the perception of inland
waterways has become significant to autonomous navigation. RGB cameras can capture …