Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …

Accurate perception is essential for advancing autonomous driving and addressing safety
challenges in modern transportation systems. Despite significant advancements in computer …

As an emerging technology and a relatively affordable device, the 4D imaging radar has
already been confirmed effective in performing 3D object detection in autonomous driving …

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

In the context of autonomous driving environment perception, multi-modal fusion plays a
pivotal role in enhancing robustness, completeness, and accuracy, thereby extending the …

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 …

The integration of cameras and millimeter-wave radar into sensor fusion algorithms is
essential to ensure robustness and cost effectiveness for vehicle pose estimation. Due to the …

Range-measuring sensors play a critical role in autonomous driving systems. While Light
Detection and Ranging (LiDAR) technology has been dominant, its vulnerability to adverse …

The current semantic segmentation algorithms suffer from encoding feature distortion and
small object feature loss. Context information exchange can effectively address the feature …

Associating radar measurements with vision measurements is essential for radar-vision
fusion. Most radar-vision association methods rely on Euclidean distance. However, these …