3 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