Cesium Tiles for High-realism Simulation and Comparing SLAM Results in
  Corresponding Virtual and Real-world Environments
Chris Beam Jincheng Zhang Nicholas Kakavitsas Collin Hague Artur Wolek Andrew Willis
This article discusses the use of a simulated environment to predict
algorithm results in the real world. Simulators are crucial in allowing
researchers to test algorithms, sensor integration, and navigation systems
without deploying expensive hardware. This article examines how the AirSim
simulator, Unreal Engine, and Cesium plugin can be used to generate simulated
digital twin models of real-world locations. Several technical challenges in
completing the analysis are discussed and the technical solutions are detailed
in this article. Work investigates how to assess mapping results for a
real-life experiment using Cesium Tiles provided by digital twins of the
experimental location. This is accompanied by a description of a process for
duplicating real-world flights in simulation. The performance of these methods
is evaluated by analyzing real-life and experimental image telemetry with the
Direct Sparse Odometry (DSO) mapping algorithm. Results indicate that Cesium
Tiles environments can provide highly accurate models of ground truth geometry
after careful alignment. Further, results from real-life and simulated
telemetry analysis indicate that the virtual simulation results accurately
predict real-life results. Findings indicate that the algorithm results in real
life and in the simulated duplicate exhibited a high degree of similarity. This
indicates that the use of Cesium Tiles environments as a virtual digital twin
for real-life experiments will provide representative results for such
algorithms. The impact of this can be significant, potentially allowing
expansive virtual testing of robotic systems at specific deployment locations
to develop solutions that are tailored to the environment and potentially
outperforming solutions meant to work in completely generic environments.