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

TL;DR

This paper reviews how autonomous indoor drones equipped with advanced physics-aware sensors and intelligent algorithms can revolutionize property assessment by providing objective, quantitative measurements instead of subjective visual inspections.

Contribution

It provides a comprehensive overview of the technical foundations and integration strategies for autonomous indoor drones in property assessment, highlighting recent innovations across multiple domains.

Findings

Enhanced platform architectures for indoor navigation

Advanced sensing modalities for material and surface characterization

Active reconstruction algorithms for strategic data collection

Abstract

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.