From Photons to Physics: Autonomous Indoor Drones and the Future of Objective Property Assessment

Fuente: arXiv
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Autori principali: Teikari, Petteri, Jarrell, Mike, Moreno, Irene Bandera, Pesola, Harri
Natura: Preprint
Pubblicazione: 2025
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author Teikari, Petteri
Jarrell, Mike
Moreno, Irene Bandera
Pesola, Harri
author_facet Teikari, Petteri
Jarrell, Mike
Moreno, Irene Bandera
Pesola, Harri
contents The convergence of autonomous indoor drones with physics-aware sensing technologies promises to transform property assessment from subjective visual inspection to objective, quantitative measurement. This comprehensive review examines the technical foundations enabling this paradigm shift across four critical domains: (1) platform architectures optimized for indoor navigation, where weight constraints drive innovations in heterogeneous computing, collision-tolerant design, and hierarchical control systems; (2) advanced sensing modalities that extend perception beyond human vision, including hyperspectral imaging for material identification, polarimetric sensing for surface characterization, and computational imaging with metaphotonics enabling radical miniaturization; (3) intelligent autonomy through active reconstruction algorithms, where drones equipped with 3D Gaussian Splatting make strategic decisions about viewpoint selection to maximize information gain within battery constraints; and (4) integration pathways with existing property workflows, including Building Information Modeling (BIM) systems and industry standards like Uniform Appraisal Dataset (UAD) 3.6.
format Preprint
id arxiv_https___arxiv_org_abs_2508_01965
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle From Photons to Physics: Autonomous Indoor Drones and the Future of Objective Property Assessment
Teikari, Petteri
Jarrell, Mike
Moreno, Irene Bandera
Pesola, Harri
Robotics
Computer Vision and Pattern Recognition
I.2.9; I.4.8; I.2.10; C.3; J.2
The convergence of autonomous indoor drones with physics-aware sensing technologies promises to transform property assessment from subjective visual inspection to objective, quantitative measurement. This comprehensive review examines the technical foundations enabling this paradigm shift across four critical domains: (1) platform architectures optimized for indoor navigation, where weight constraints drive innovations in heterogeneous computing, collision-tolerant design, and hierarchical control systems; (2) advanced sensing modalities that extend perception beyond human vision, including hyperspectral imaging for material identification, polarimetric sensing for surface characterization, and computational imaging with metaphotonics enabling radical miniaturization; (3) intelligent autonomy through active reconstruction algorithms, where drones equipped with 3D Gaussian Splatting make strategic decisions about viewpoint selection to maximize information gain within battery constraints; and (4) integration pathways with existing property workflows, including Building Information Modeling (BIM) systems and industry standards like Uniform Appraisal Dataset (UAD) 3.6.
title From Photons to Physics: Autonomous Indoor Drones and the Future of Objective Property Assessment
topic Robotics
Computer Vision and Pattern Recognition
I.2.9; I.4.8; I.2.10; C.3; J.2
url https://arxiv.org/abs/2508.01965