A multi-platform active debris removal mission planning method based on DCOP with chain topology

Abstract

In this work, a distributed multi-platform active debris removal mission planning task is formulated as a distributed constrained optimization problem (DCOP), and a novel Synchronous Incomplete Searching Algorithm under Chain Topology (SISACT) is proposed. We envision a distributive cooperative mission planning scenario where multiple debris removal platforms generate individual mission sub-plans on how to remove a subset of assigned debris subject to constraints on mission duration and orbit transfer cost. The overall goal is to maximize the aggregate reward for debris removal while avoiding conflicts among sub-plans. To resolve the potential conflicts, multiple platforms must communicate each other intensively. The proposed SISACT algorithm can reduce the inter-platform communication burdens by inducing a fully connected constraint graph into a chain graph with domain assignment. SISACT is designed to focus on global collaboration among the platforms for mission plan partitioning while leveraging existing single platform mission planning algorithms to provide details of the sub-plans. Simulation with a realistic active debris removal scenario has been carried out. It is shown that the proposed SISACT algorithm can optimize the overall reward of the mission while satisfying all the constraints. This validates the effectiveness of SISACT. • A new multi-platform ADR mission planning is proposed based on DCOP. • A new DCOP model with fully-connected all-hard constraint graph is presented. • Proposed method can satisfy all constraints without changing solution frequently. • Tests on Iridium33 debris set with 4 platforms verify its efficiency.