Orbital Manoeuvring Optimization Techniques for Collision Avoidance through Decentralized Algorithms

Traditional centralized control schemes, while effective in less congested environments, are proving inadequate in today’s increasingly dense and dynamic orbital landscapes, facing significant challenges in terms of scalability, flexibility, and responsiveness to the fast-changing conditions of space traffic. The goal of this paper is to present a novel framework for decentralized optimization of orbital manoeuvring techniques for cooperative collision avoidance, focusing on a scalable and adaptive approach that caters to the dynamic and heterogeneous nature of space traffic. Optimizing resources such as energy consumption, propellant usage, and data exchange through autonomous allocation and utilization of the satellites’ subsystems. By leveraging real-time data and predictive modeling, these algorithms enable satellites to make informed decisions about when and how to manoeuvre to avoid potential collisions. Not only improving the responsiveness of the system to unforeseen changes but also significantly reducing the communication overhead and delays associated with centralized control. Results are presented on the benefits and drawbacks of such an approach under a varied range of operational conditions and complexities, facilitating efficient decision-making and resource allocation tailored to each unique situation. Through validation with conventional thrust based manoeuvring techniques, comparisons are shown and an innovative procedure is proposed. Furthermore, this research aims to lay the groundwork for future advancements in spacecraft navigation, promising enhanced safety and efficiency.     «

Traditional centralized control schemes, while effective in less congested environments, are proving inadequate in today’s increasingly dense and dynamic orbital landscapes, facing significant challenges in terms of scalability, flexibility, and responsiveness to the fast-changing conditions of space traffic. The goal of this paper is to present a novel framework for decentralized optimization of orbital manoeuvring techniques for cooperative collision avoidance, focusing on a scalable and adapt...     »