System and method for controlling search operations by swarms of autonomous agents

Abstract

A multi-agent control system coordinates autonomous agents to efficiently search two-dimensional and three-dimensional surfaces for targets. The system employs a multi-phase decentralized control strategy including deployment, circle formation, and spiral search phases. During circle formation, agents use a distributed consensus-based auction algorithm with wind-aware or current-aware cost calculations to assign themselves to evenly-spaced angular positions around a mission center. Agents then execute search trajectories with adjacent passes spaced at twice the sensor footprint radius to ensure complete coverage without gaps or overlaps. For two-dimensional surfaces, trajectories follow Archimedean spirals proven optimal for targets with radially-symmetric probability distributions. For three-dimensional surfaces, trajectories follow geodesic coils that conform to surface geometry using geodesic distance fields and level-set projection. The system includes obstacle avoidance capabilities using best-gap selection. Applications include search and rescue, reconnaissance, environmental monitoring, and surveillance.

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