Co-Optimization and Planning of Cyber-Physical Aerospace Systems

To address the higher planning layer we propose a cost function of cyber and physical parameters to optimize an Unmanned Aircraft system (UAS) trajectory for a pipeline surveillance mission. Optimization parameters are UAV velocity and mission-critical surveillance task execution rate. Metrics for pipeline image information, energy, cyber utilization, and time comprise the cost function and Pareto fronts are analyzed to gain insight into cyber and physical tradeoffs for mission success.

Total Cost function

Finally, the cost function is optimized using numerical methods, and results from several cost weightings and Pareto front analyses are tabulated. We show that increased mission success can be achieved by considering both cyber and physical parameters together.

Pareto Front