Multi-criterion multi-UAV task allocation under dynamic conditions

Abstract

Multi-UAV systems are essential in accomplishing specific tasks across various research applications. UAVs can be used in search and rescue (SR), which requires them to explore disaster areas and rescue survivors. A significant challenge in such a scenario is allocating tasks to UAVs to support as many survivors as possible. The allocation of tasks to a multi-UAV system is a highly intricate issue that falls under the NP-hard classification. Dealing with multiple attributes and constraints for tasks and UAVs can complicate the problem. Based on several limiting factors and distinctive characteristics, this paper proposes a compromised task allocation (TA) approach for multi-UAVs operating in SR scenarios. The proposed algorithm enhances the performance impact (PI) algorithm by incorporating compromised PI (CPI) with specific constraints. Additionally, CPI is extended to compromised dynamic PI (CDPI) to handle any new tasks that may arise during task execution to accommodate dynamic events. Simulation results demonstrate a performance improvement of 22% in task allocation and 28.57% for task prioritization as compared with the PI algorithm.