Research on the effectiveness of the operator's actions

The article examines the current effectiveness of the Unmanned Systems Forces in the context of the rapid development and large-scale deployment of unmanned and robotic complexes of various types (aerial, ground, and others). The research focuses on the manual drone control model, where the human operator acts as the central element of the control loop. The scientific objective of this study is to explore the operator’s capabilities, functional requirements, and cognitive workload in performing higher-level control functions, while the hardware–software complex (HSC) provides lower-level technical control. Experimental results demonstrate the high efficiency of drone control performed by a well-trained operator capable of independently orienting without GPS, identifying and selecting targets, evaluating mission status, generating control commands, and maintaining situational awareness through conscious information exchange. A key factor contributing to mission success is the operator’s ability to learn, relearn, and self-learn, which enhances operational performance and adaptability in combat conditions. At the same time, several constraints have been identified, including limited information-processing speed, reaction time, and decision-making rate, as well as the influence of the operator’s psychological and emotional state on combat effectiveness. Future research will focus on developing and analyzing automated and fully automatic control models for robotic systems, integrating machine vision, artificial intelligence, and adaptive human–machine interaction technologies to improve mission reliability and efficiency.