Optimization of Dynamic Task Allocation forMulti-UAV Systems: Search and Rescue Scenario

Abstract Unmanned aerial vehicles (UAVs) are becomingincreasingly popular due to their versatility and cost-effectivenessand are used in various scenarios, such as sea exploration andsearch and rescue missions. Urban search and rescue requires aprompt and effective response to unforeseen events like faultsin UAVs, changes in task duration and deadline, new UAVarrivals, and task deletions. This paper extends the compromiseddynamic performance impact (CDPI) algorithm and introducesan enhanced CDPI (ECDPI) that can effectively handle dynamicevents during task execution. For dynamic event handling inthe ECDPI algorithm, the communication and conflict resolutionphase uses the time cost vector of each UAV for its assignedtask, as well as improvements in the detect dynamic activity function. In addition, limitations and cases against dynamicevents are discussed to exploit the proposed scheme effectively.The simulation results demonstrate that ECDPI is highly effectiveat handling dynamic events during the task execution phase