Collaborative Threat-Aware Autonomy (CTAA)
For operators of unmanned vehicle teams facing dynamic adversarial threats, this framework offers a practical method to enhance mission success through role differentiation and coordinated path planning.
The paper proposes a role-differentiated multi-agent framework for collaborative threat-aware trajectory planning in unmanned vehicle teams, achieving improved mission success probability by assigning distinct roles (intercept, escort, decoy) and using a reactive guidance law. The approach leverages probabilistic redundancy and threat saturation to reduce individual exposure to adversarial Weapon Engagement Zones.
Navigating teams of unmanned vehicles through environments containing dynamic, adversarial Weapon Engagement Zones~(WEZs) poses a fundamental challenge to mission success: a single vehicle, however capable its onboard guidance, remains a single point of failure. This paper presents a role-differentiated multi-agent framework for collaborative threat-aware trajectory planning in which a fleet of Autonomous Collaborative Platforms~(ACPs) is assigned distinct roles primary intercept, escort, and decoy to improve team-level mission success probability while managing individual WEZ exposure. Each ACP independently employs a reactive guidance law derived from the Collision Sphere Boundary for Evader Zero-Set~(CSBEZ), which accounts for pursuer maneuverability constraints imposed by minimum turn radius, and steers the vehicle toward the safest heading that also makes progress toward its goal. Role assignment and spatial route separation induce two complementary effects: probabilistic redundancy, in which $N$ independent paths raise the team success probability and threat saturation, in which lower-priority escorts and decoys draw adversary attention and free the primary vehicle to transit uncontested.