OrbitZoo: Multi-Agent Reinforcement Learning Environment for Orbital Dynamics

• URL: http://arxiv.org/abs/2504.04160v1
• Date: Sat, 05 Apr 2025 12:44:21 GMT
• Title: OrbitZoo: Multi-Agent Reinforcement Learning Environment for Orbital Dynamics
• Authors: Alexandre Oliveira, Katarina Dyreby, Francisco Caldas, Cláudia Soares,
• Abstract summary: OrbitZoo is a versatile multi-agent RL environment built on a high-fidelity industry standard library.<n>It supports scenarios like collision avoidance and cooperative maneuvers, and ensures robust and accurate orbital dynamics.<n>It is validated against a real satellite constellation, Starlink, achieving a Mean Absolute Percentage Error (MAPE) of 0.16% compared to real-world data.
• Score: 43.410962336636224
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The increasing number of satellites and orbital debris has made space congestion a critical issue, threatening satellite safety and sustainability. Challenges such as collision avoidance, station-keeping, and orbital maneuvering require advanced techniques to handle dynamic uncertainties and multi-agent interactions. Reinforcement learning (RL) has shown promise in this domain, enabling adaptive, autonomous policies for space operations; however, many existing RL frameworks rely on custom-built environments developed from scratch, which often use simplified models and require significant time to implement and validate the orbital dynamics, limiting their ability to fully capture real-world complexities. To address this, we introduce OrbitZoo, a versatile multi-agent RL environment built on a high-fidelity industry standard library, that enables realistic data generation, supports scenarios like collision avoidance and cooperative maneuvers, and ensures robust and accurate orbital dynamics. The environment is validated against a real satellite constellation, Starlink, achieving a Mean Absolute Percentage Error (MAPE) of 0.16% compared to real-world data. This validation ensures reliability for generating high-fidelity simulations and enabling autonomous and independent satellite operations.

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