Unmanned aerial vehicle (UAV) systems can fail during civil and military operations. This presents a significant challenge for human teleoperators (remote pilots) in determining task reallocation after member loss within the fleet. To alleviate the high cognitive load on teleoperators in critical situations, a decentralized strategy was developed to resolve the combined task assignment and vehicle routing problems. This Integrated Consensus Framework (ICF) not only solves the combined problem but also adds a unique ability to identify the loss of a vehicle and dynamically reroute agents to abandoned tasks to achieve a satisfactory solution. ICF is a two-tiered approach that combines a novel algorithm, the Caravan Auction (CarA) algorithm, with a path-planning strategy to identify when UAVs are lost and reallocate orphaned tasks. The CarA Algorithm consists of three phases: auction, consensus, and validation phases. An experiment using Monte Carlo simulations was conducted to determine the performance of ICF. Teleoperators assigned to complete multiple tasks with UAVs in dangerous environments can allow the proposed system to perform task assignments and reallocation while offering only supervisory control as needed. The results indicate this novel approach provides comparable performance to existing strategies, doing so with the addition of randomized UAV loss.
This study focuses on designing and testing a formation guidance system for a UCAV as a wingman to an F-16 fighter jet. A critical assessment of the UCAV autopilot revealed areas for improvement, which were addressed to refine the stable foundation of the autopilot for implementing the guidance system. This system uses PID controllers to minimise the along-track, cross-track, and vertical-track errors during standard manoeuvres. The system performed exceptionally well in the vertical (z) direction but showed robustness challenges in the along-track (x) and cross-track (y) directions under wind disturbances. A notable outcome was the identification of a novel mathematical relationship between the along-track offset command and its gains, offering a pathway for advanced formation systems. These findings pave the way for future enhancements in diverse formation operations.