5 papers
M2-SMap: Memory-Efficient Semantic Mapping with Hierarchical Multi-Model Representation
QiYing Deng, ZhongLai Wang, Yuan Gao +1
Dense point cloud maps, as a typically used mapping representation, are difficult to deploy on resource-constrained robots because their memory consumption grows rapidly with scene…
A2VISR: An Active and Adaptive Ground-Aerial Localization System Using Visual Inertial and Single-Range Fusion
Sijia Chen, Wei Dong
It's a practical approach using the ground-aerial collaborative system to enhance the localization robustness of flying robots in cluttered environments, especially when visual sen…
Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline
Zhaoying Wang, Xingxing Zuo, Wei Dong
Lightweight long-range mapping is critical for safe navigation of UAV swarms in large-scale unknown environments. Traditional stereo vision systems with fixed short baselines face…
Particle-based Instance-aware Semantic Occupancy Mapping in Dynamic Environments
Gang Chen, Zhaoying Wang, Wei Dong +1
Representing the 3D environment with instance-aware semantic and geometric information is crucial for interaction-aware robots in dynamic environments. Nevertheless, creating such…
Towards Aerial Collaborative Stereo: Real-Time Cross-Camera Feature Association and Relative Pose Estimation for UAVs
Zhaoying Wang, Wei Dong
The collaborative visual perception of multiple Unmanned Aerial Vehicles (UAVs) has increasingly become a research hotspot. Compared to a single UAV equipped with a short-baseline…