Autonomous vehicles integrate complex software stacks for realizing the necessary iterative
perception, planning, and action operations. One of the foundational layers of such stacks is …

Lane detection is one of the fundamental modules in self-driving. In this paper we employ a
transformer-only method for lane detection, thus it could benefit from the blooming …

Conventional map-matching (MM) algorithms take blind eyes to the complexity in realistic
traffic conditions and hence present significant limitations in distinguishing the detailed …

Matching high definition (HD) map and real-time sensor data, which is crucial for map-based
intelligent vehicle localization, usually requires robust and distinct road features extracted …

In this paper, we propose a visual marker-aided LiDAR/IMU/encoder integrated odometry,
Marked-LIEO, to achieve pose estimation of mobile robots in an indoor long corridor …

The computer-based navigation system computes the object's position, speed, and direction
in real-time. In the last decades, many researchers, companies, and industries have been …

The development of smart vehicles has increased the demand for high-definition road maps.
However, traditional road maps for vehicle navigation systems are not sufficient to meet the …

Quickly grasping the surrounding environment's information and the location of the vehicle is
the key to achieving automatic driving. However, accurate and robust localization and …

Recovering the point cloud maps of large-scale scenes from multi-sensor data is the
fundamental building block of numerous 3D related applications. Available SLAM …

The ego vehicle's location is critical for a variety of autonomous functions, the most notable
of which are lane departure warning systems (LDWS). LDWS typically detect lane …