Adaptive Ground Control System of Multiple-UAV Operators in a Simulated Environment

Area of Science:

• Aerospace Engineering
• Human-Computer Interaction
• Cognitive Psychology

Background:

• Managing multiple unmanned aerial vehicles (UAVs) presents significant operator workload challenges.
• Conventional Ground Control Systems (CGCS) may not adequately support complex, multi-UAV missions.
• Real-time operator gaze, UAV status, and mission data are crucial for efficient control.

Purpose of the Study:

• To develop and evaluate an Adaptive Ground Control System (AGCS) designed to decrease operator workload during multiple UAV operations.
• To compare the performance and workload of the AGCS against a Conventional Ground Control System (CGCS).
• To assess the system's effectiveness using objective performance metrics and subjective operator feedback.

Main Methods:

• A human-in-the-loop experiment was conducted with 30 volunteers.
• Participants operated multiple UAVs in reconnaissance and strike missions using both AGCS and CGCS.
• Eye-tracking data (pupil diameter, gaze indicator) and task performance metrics were collected.

Main Results:

• The AGCS demonstrated statistically significant improvements in mission completion rates (97.3% vs. 95.4%) and mission success rates (90.4% vs. 88.4%).
• Operator workload was significantly reduced, as indicated by pupil diameter and gaze data (α = 0.05).
• Participants reported positive subjective experiences with the AGCS.

Conclusions:

• The developed AGCS effectively reduces operator workload and enhances mission performance in multi-UAV operations.
• The system shows potential for future advancements based on experimental findings and expert feedback.
• AGCS represents a significant step towards safer and more efficient multi-UAV mission execution.