Title
Analysis of Using Mixed Reality Simulations for Incremental Development of Multi-UAV Systems
Abstract
Developing complex robotic systems requires expensive and time-consuming verification and testing which, especially in a case of multi-robot unmanned aerial systems (UASs), aggregates risk of hardware failures and may pose legal issues in experiments where operating more than one unmanned aircraft simultaneously is required. Thus, it is highly favorable to find and resolve most of the eventual design flaws and system bugs in a simulation, where their impacts are significantly lower. On the other hand, as the system development process approaches the final stages, the fidelity of the simulation needs to rise. However, since some phenomena that can significantly influence the system behavior are difficult to be modeled precisely, a partial embodiment of the simulation in the physical world is necessary. In this paper, we present a method for incremental development of complex unmanned aerial systems with the help of mixed reality simulations. The presented methodology is accompanied with a cost analysis to further show its benefits. The generality and versatility of the method is demonstrated in three practical use cases of various aviation systems development: (i) an unmanned system consisting of heterogeneous team of autonomous unmanned aircraft; (ii) a system for verification of collision avoidance methods among fixed wing unmanned aerial vehicles; and (iii) a system for planning collision-free paths for light-sport aircraft.
Year
DOI
Venue
2019
10.1007/s10846-018-0875-8
Journal of Intelligent and Robotic Systems
Keywords
Field
DocType
UAS development, Mixed-reality simulations, UAS applications, Multi-UAV systems
Fidelity,Use case,Iterative and incremental development,Aviation,Collision,Control engineering,Engineering,Mixed reality,Cost analysis,Generality
Journal
Volume
Issue
ISSN
95.0
1
1573-0409
Citations 
PageRank 
References 
0
0.34
12
Authors
3
Name
Order
Citations
PageRank
Martin Selecký1202.32
Jan Faigl233642.34
Milan Rollo3455.83