Validating Terrain Models in Digital Twins for Trustworthy sUAS Operations

TL;DR

This paper presents a comprehensive validation process for terrain models in Environmental Digital Twins, crucial for safe and reliable sUAS operations in complex environments, addressing real-world uncertainties and sensor inaccuracies.

Contribution

It introduces a 3-Dimensional validation workflow for terrain models in Digital Twins, integrating software engineering principles with real-world testing for sUAS applications.

Findings

Validated terrain models improve sUAS safety in complex environments

The workflow effectively identifies model inaccuracies and sensor errors

Demonstrated approach enhances trustworthiness of digital twin components

Abstract

With the increasing deployment of small Unmanned Aircraft Systems (sUAS) in unfamiliar and complex environments, Environmental Digital Twins (EDT) that comprise weather, airspace, and terrain data are critical for safe flight planning and for maintaining appropriate altitudes during search and surveillance operations. With the expansion of sUAS capabilities through edge and cloud computing, accurate EDT are also vital for advanced sUAS capabilities, like geolocation. However, real-world sUAS deployment introduces significant sources of uncertainty, necessitating a robust validation process for EDT components. This paper focuses on the validation of terrain models, one of the key components of an EDT, for real-world sUAS tasks. These models are constructed by fusing U.S. Geological Survey (USGS) datasets and satellite imagery, incorporating high-resolution environmental data to support mission tasks. Validating both the terrain models and their operational use by sUAS under real-world conditions presents significant challenges, including limited data granularity, terrain discontinuities, GPS and sensor inaccuracies, visual detection uncertainties, as well as onboard resources and timing constraints. We propose a 3-Dimensions validation process grounded in software engineering principles, following a workflow across granularity of tests, simulation to real world, and the analysis of simple to edge conditions. We demonstrate our approach using a multi-sUAS platform equipped with a Terrain-Aware Digital Shadow.