However, maintaining high-precision localization in complex scenarios, such as degraded environments or when dynamic objects are present, remains a significant challenge. To address this issue, we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and ...
A semantic ICP approach was presented by Yin et al. (2023). This method uses the 3D geometry and semantic data of a BIM model to achieve a reliable 3D LiDAR localization method. Their system suggests a BIM-to-Map conversion, turning the 3D model into a point cloud that is semantically e...
Autonomous driving has been widely applied in commercial and industrial applications, along with the upgrade of environmental awareness systems. Tasks such as path planning, trajectory tracking, and obstacle avoidance are strongly dependent on the abilit
This matching is one of the steps for the localization. Features also give semantic information about the environment. The detection of a corner or a door indicates a potential encounter with human beings. Aware of this “danger” area, the robot will be able to adapt its speed and define ...
In this work, we present a semantic situation awareness system for multirotor aerial robots equipped with a 2D LIDAR sensor, focusing on the understanding of the environment, provided to have a drift-free precise localization of the robot (e.g. given by GNSS/INS or motion capture system). ...
scientificreports OPEN Real time object detection using LiDAR and camera fusion for autonomous driving Haibin Liu , Chao Wu & Huanjie Wang * Autonomous driving has been widely applied in commercial and industrial applications, along with the upgrade of environmental awareness ...
scientificreports OPEN Real time object detection using LiDAR and camera fusion for autonomous driving Haibin Liu , Chao Wu & Huanjie Wang * Autonomous driving has been widely applied in commercial and industrial applications, along with the upgrade of environmental awareness ...
OpenSight utilizes 2D-3D geometric priors for the initial discernment and localization of generic objects, followed by a more specific semantic interpretation of the detected objects. The process begins by generating 2D boxes for generic objects from the accompanying camera images of LiDAR. These 2D ...
semantic interpretation could leverage research on real-time applications like self-localization and traffic monitoring, for which we provide an all-in-one dataset. In addition, we provide different kinds of labels, including semantic labels and single instances of relevant objects. Compared with image...
Additionally, the NVIDIA NX was tasked with computing the proposed localization method, map construction, and landing site selection, and communicating the motion requirements of the UAV to the Pixhawk flight control computer, as illustrated in Figure 7. Figure 7. Schematic diagram of the UAV ...