9 accepted papers
Although Gaussian scene representation has achieved remarkable success in tracking and mapping, most existing methods are confined to single-agent systems. Current multi-agent solutions typically rely on centralized architectures, which struggle to account for communication bandwidth constraints. Fu
This paper presents a novel collaborative online dense mapping system for multiple Unmanned Aerial Vehicles (UAVs). The system confers two primary benefits: it facilitates simultaneous UAVs co-localization and real-time dense map reconstruction, and it recovers the metric scale even in GNSS-denied c
Unmanned aerial vehicles (UAVs) equipped with LiDAR, camera, and Inertial Measurement Unit sensors are increasingly utilized for real-time dense reconstruction in large-scale rescue operations and environmental monitoring, among others. However, achieving algorithmic robustness remains challenging d
Real-time dense reconstruction using Unmanned Aerial Vehicle (UAV) is becoming increasingly popular in large-scale rescue and environmental monitoring tasks. However, due to the energy constraints of a single UAV, the efficiency can be greatly improved through the collaboration of multi-UAVs. Nevert…
Recently, cross-source point cloud registration from different sensors has become a significant research focus. Although current methods have advanced homogenous point cloud registration, challenges persist in the cross-source domain due to varying point cloud densities from different sensors and mi
With the rapidly developing unmanned aerial vehicles, the requirements of generating maps efficiently and quickly are increasing. To realize online mapping, we develop a real-time dense mapping framework named DenseFusion which can incrementally generates dense geo-referenced 3D point cloud, digital…
SLAM technology has recently seen many successes and attracted the attention of high-technological companies. However, how to unify the interface of existing or emerging algorithms, and effectively perform benchmark about the speed, robustness and portability are still problems. In this paper, we pr…
This paper presents an algorithm which can generate live digtial surface model (DSM) during the flight based on simultaneous localization and mapping (SLAM). We process the keyframe which is output by a monocular SLAM system to generate a local DSM, and fuse the local DSM to the global tiled DSM inc…
In this paper we present a real-time approach to stitch large-scale aerial images incrementally. A monocular SLAM system is used to estimate camera position and attitude, and meanwhile 3D point cloud map is generated. When GPS information is available, the estimated trajectory is transformed to WGS8…