Distributed Cooperative Task Allocation for Many-to-Few On-Orbit Servicing Missions

This paper investigates cooperative task allocation for multi-satellite clusters under onboard functional payload constraints in many-to-few low Earth orbit non-cooperative servicing scenarios involving heterogeneous space targets. Although the servicing satellite cluster has a numerical advantage, the effectiveness of a single satellite is limited by orbital maneuver cost and the stringent requirements of onboard functional payload systems on rendezvous accuracy and interaction timing. As a result, multiple satellites are generally required to cooperate to establish local numerical superiority for effective task execution. Meanwhile, differences in object strategic importance and resistance capability may lead to excessive resource concentration on high-value objects, thereby degrading overall operational efficiency. To address these issues, an existing multi-satellite cooperative task planning framework is adopted to characterize the matching relationship between resource supply and task demand by jointly considering maneuver cost, target value heterogeneity, and coalition-size requirements. On this basis, a distributed cooperative mechanism is introduced to enable the satellite cluster to adaptively form coordinated task coalitions matched to object value. Simulation results show that, in representative many-to-few LEO servicing scenarios, the resulting allocation scheme can establish local cooperative resource concentration while satisfying full target coverage and no-idle-satellite constraints. It also suppresses excessive competition for high-value objects and improves the balance of resource utilization, thereby demonstrating the effectiveness of the proposed approach for cooperative task allocation in multi-satellite LEO servicing scenarios.