The perception of autonomous vehicles has to be efficient, robust, and cost-effective.
However, cameras are not robust against severe weather conditions, lidar sensors are …

Radars, due to their robustness to adverse weather conditions and ability to measure object
motions, have served in autonomous driving and intelligent agents for years. However …

In the field of 3D object detection for autonomous driving LiDAR-Camera (LC) fusion is the
top-performing sensor configuration. Still LiDAR is relatively high cost which hinders …

Obstacle perception based on radar sensor has drawn wide attentions in autonomous
driving due to robust performance and low cost. It is significant to utilize fusion, eg, camera …

Due to millimeter-wave (MMW) radar's ability to directly acquire spatial positions and velocity
information of objects, as well as its robust performance in adverse weather conditions, it …

In autonomous driving systems, cameras and light detection and ranging (LiDAR) are two
common sensors for object detection. However, both sensors can be severely affected by …

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …

Abstract Object detection utilizing Frequency Modulated Continuous Wave radar is
becoming increasingly popular in the field of autonomous systems. Radar does not possess …

In this paper we present a novel radar-camera sensor fusion framework for accurate object
detection and distance estimation in autonomous driving scenarios. The proposed …

Fusion of multiple sensor modalities such as camera, Lidar, and Radar, which are commonly
found on autonomous vehicles, not only allows for accurate detection but also robustifies …