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What is Adaptive Autonomy in Human-UAV Surveillance about?

This paper presents a cognitive model using Situated Fuzzy Cognitive Maps (SiFCM) to dynamically adjust the Levels of Autonomy (LOA) in human-UAV collaborative surveillance tasks based on task complexity and human cognitive states. The model aims to balance the workload of human operators with task efficiency, enhancing collaboration between humans and UAVs during complex missions. Experimental results demonstrate the effectiveness of the proposed method in optimizing human-UAV teamwork in multi-target surv

Author

Gilson Macedo

Language

EN