Related papers: MmWave Radar Point Cloud Segmentation using GMM in…
Millimeter wave (mmWave) radars have attracted significant attention from both academia and industry due to their capability to operate in extreme weather conditions. However, they face challenges in terms of sparsity and noise…
Millimeter-wave (mmw) radar is indispensable for Intelligent Transportation Systems (ITS), which can monitor traffic conditions in all weathers. An end-to-end simulation method for mmw radar monitoring and identification at traffic…
The millimeter-wave radar sensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdoor mobile robotics. However, the radar point clouds are…
Complementary to prevalent LiDAR and camera systems, millimeter-wave (mmWave) radar is robust to adverse weather conditions like fog, rainstorms, and blizzards but offers sparse point clouds. Current techniques enhance the point cloud by…
The 4D millimeter-wave (mmWave) radar, with its robustness in extreme environments, extensive detection range, and capabilities for measuring velocity and elevation, has demonstrated significant potential for enhancing the perception…
Millimeter-wave (mmWave) radar has attracted significant attention in robotics and autonomous driving. However, despite the perception stability in harsh environments, the point cloud generated by mmWave radar is relatively sparse while…
This paper introduces in detail the effective method of comprehensive target judgment by using radar RA map and point cloud map. Different output of radar can effectively judge the road boundary of target and the relative coordinates of…
High-resolution radar sensors are able to resolve multiple detections per object and therefore provide valuable information for vehicle environment perception. For instance, multiple detections allow to infer the size of an object or to…
Vehicular communication systems operating in the millimeter wave (mmWave) band are highly susceptible to signal blockage from dynamic obstacles such as vehicles, pedestrians, and infrastructure. To address this challenge, we propose a…
Millimetre-wave (mmWave) radars can generate 3D point clouds to represent objects in the scene. However, the accuracy and density of the generated point cloud can be lower than a laser sensor. Although researchers have used mmWave radars…
This paper presents a framework for semantic segmentation on sparse sequential point clouds of millimeter-wave radar. Compared with cameras and lidars, millimeter-wave radars have the advantage of not revealing privacy, having a strong…
With autonomous driving developing in a booming stage, accurate object detection in complex scenarios attract wide attention to ensure the safety of autonomous driving. Millimeter wave (mmWave) radar and vision fusion is a mainstream…
Large driving datasets are a key component in the current development and safeguarding of automated driving functions. Various methods can be used to collect such driving data records. In addition to the use of sensor equipped research…
Millimeter-wave (mmWave) radar offers robust sensing capabilities in diverse environments, making it a highly promising solution for human body reconstruction due to its privacy-friendly and non-intrusive nature. However, the significant…
5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station and vehicles are equipped with large antenna arrays. However, radio-based positioning suffers from multipath signals generated…
LiDAR point clouds have become the most common data source in autonomous driving. However, due to the sparsity of point clouds, accurate and reliable detection cannot be achieved in specific scenarios. Because of their complementarity with…
Point cloud registration sits at the core of many important and challenging 3D perception problems including autonomous navigation, SLAM, object/scene recognition, and augmented reality. In this paper, we present a new registration…
In robotic inspection of aviation parts, achieving accurate pairwise point cloud registration between scanned and model data is essential. However, noise and outliers generated in robotic scanned data can compromise registration accuracy.…
This paper explores an integrated approach for improved sensing and positioning with applications in air traffic management (ATM) and in the Advanced Surface Movement Guidance and Control System (A-SMGCS). The integrated approach includes…
Environmental perception with the multi-modal fusion of radar and camera is crucial in autonomous driving to increase accuracy, completeness, and robustness. This paper focuses on utilizing millimeter-wave (MMW) radar and camera sensor…