Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors

Sensors (Basel). 2022 Dec 3;22(23):9462. doi: 10.3390/s22239462.

Abstract

Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time volume estimation based on a custom platform equipped with depth and tracking cameras. Its performance has been tested in different application-oriented scenarios and compared against measurements and state-of-the-art photogrammetry. The comparison showed that the developed architecture is able to provide estimates fully comparable with the benchmark, resulting in a quick, reliable and cost-effective solution to the problem of volumetric estimates within the functioning range of the exploited sensors.

Keywords: Intel RealSense; Kalman filtering; close-range remote sensing; drones; near real-time three-dimensional scene reconstruction; volume estimation.

MeSH terms

  • Photogrammetry*
  • Remote Sensing Technology* / methods

Grants and funding

This work has been co-founded by the Italian Ministry of University and Research, the Italian Aerospace Research Centre and Analyst Group under the aegis of the project “Crowd for the Environment”.