Multi-satellite Task Planning Based on Dynamic Collaboration with Multiple Boundary Constraints

The design of efficient and fast autonomous task planning algorithms is the core of achieving satellite high maneuverability autonomous task planning with multiple boundary constraints. This article studies a satellite high maneuverability autonomous task planning algorithm with multiple boundary constraints, using a distributed method to allocate and execute observation tasks released on the ground independently, reducing the pressure on ground personnel to control satellites, and achieving full utilization of satellite observation resources. After receiving various tasks, satellites can independently complete planning tasks such as regional target segmentation, multi-objective timing arrangement, task execution/switching process planning, and task conflict selection based on environmental information and their own state information. This article simulates and verifies the algorithm through typical application scenarios, demonstrating its effectiveness.