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Pengcheng Han

5 accepted papers

2026

CoMA-SLAM: Collaborative Multi-Agent Gaussian SLAM with Geometric Consistency

AAAI 2026technical

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

Cited by 0SourcePDFScholar
2025

CODE: COllaborative Visual-UWB SLAM for Online Large-Scale Metric DEnse Mapping

IROS 2025

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

Cited by 0SourceScholar
2020

DenseFusion: Large-Scale Online Dense Pointcloud and DSM Mapping for UAVs

IROS 2020poster

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…

Cited by 11SourceScholar
2019

TerrainFusion: Real-time Digital Surface Model Reconstruction based on Monocular SLAM

IROS 2019poster

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…

Cited by 19SourceScholar