A Distributed Platform for Flight Dynamics Simulation of Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) can be widely used in a variety of application areas. Examples include remote sensing, delivering packages to remote locations, collecting data or intelligence, searching or surveying geographic areas, performing tasks otherwise to be difficult or dangerous by traditional ways, etc. There are several essential components and functions onboard UAVs, including path planning, flight control, propulsion, and energy management. Testing of these components and functions in a high-fidelity virtual environment will help developers make timely corrections or updates to control algorithms and software codes, if needed, and provide confidence to the designer, before moving to field tests, because UAV testing is costly and related to safety and reliability. This paper presents a real-time distributed computing platform that is suited to flight dynamics and control simulation of UAVs, considering path planning, flight control, propulsion, and energy management. The platform includes real-time computing components for flight dynamic simulation, control implementation in different ways, data visualization, and data communication, by leveraging available design and testing tools. The detailed methodology and components are described in the paper, and a comprehensive case study is used to demonstrate the capability and applications of this platform in different scenarios. The simulation results of flight missions, involving dynamics of several key components in an autonomous UAV, are presented. Further development to this platform may include adding the hardware/software interfaces to facilitate distributed simulation and teaming coordination of UAV swarms as well as incorporating camera-based obstacle detection and avoidance techniques. With access to the cameras or other sensors, the mission capabilities can further be improved by leveraging the analytics processing video streaming data. Advanced solvers for integrated operation of path planning, flight control and energy management can then be introduced for more precise control on the state of the vehicle. This will also pave the way for the development of energy-optimized, fault-tolerant predictive control and autonomous teaming of many manned and unmanned vehicles.