arXiv:2211.08013
Drone-based Volume Estimation in Indoor Environments
원문 초록
Volume estimation in large indoor spaces is an important challenge in robotic inspection of industrial warehouses. We propose an approach for volume estimation for autonomous systems using visual features for indoor localization and surface reconstruction from 2D-LiDAR measurements. A Gaussian Process-based model incorporates information collected from measurements given statistical prior information about the terrain, from which the volume estimate is computed. Our algorithm finds feasible trajectories which minimize the uncertainty of the volume estimate. We show results in simulation for the surface reconstruction and volume estimate of topographic data.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Anti-Aliased 2D Gaussian Splatting
Multi-view Surface Reconstruction Using Normal and Reflectance Cues
VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural Surface Reconstruction
A Divide-and-Conquer Approach for Global Orientation of Non-Watertight Scene-Level Point Clouds Using 0-1 Integer Optimization
End-to-end Cortical Surface Reconstruction from Clinical Magnetic Resonance Images
EnviKal-Loc: Sub-10m Indoor LoRaWAN Localization using an Environmental-Aware Path Loss and Adaptive RSSI Smoothing
토론
이 논문과 연결된 포럼 글이 아직 없습니다.