@inproceedings{stevenson2022_icssa,

title = {An Intelligent System for Robust Decision-Making in the All-vs-All Conjunction Screening Problem},

author = {Luis Sánchez Fernandez-Mellado and Emma Stevenson and Rodriguez-Fernandez and Massimiliano Vasile and David Camacho},

year  = {2022},

date = {2022-04-01},

urldate = {2022-04-01},

booktitle = {3rd IAA Conference on Space Situational Awareness (ICSSA)},

address = {Madrid, Spain},

abstract = {The progressive increase of traffic in space demands new approaches for supporting automatic and robust operational decisions. CASSANDRA, Computational Agent for Space Situational Awareness aNd Debris Remediation Automation, is an intelligent system for Space Environment Management (SEM) intended to assist operators with the management of space traffic by providing robust decision-making support. This paper will present the automatic conjunction screening and collision avoidance manoeuvre pipeline within CASSANDRA, connecting the some of CASSANDRA's modules: Automated Conjunction Screening (ACS), Robust State Estimation (RSE), Intelligent Decision Support System (IDSS) and Collision Avoidance Manoeuvres (CAM). The pipelines allows to screen the catalogue to detect potential conjunctions, perform a detailed analysis of the encounter accounting for uncertainty (aleatory and epistemic) and new observations, provide robust decisions based on the available information and, if necessary, proposed robust optimal CAMs and analyse the impact of the new orbit on the background population. This paper will present the pipeline described above along with an example that illustrates how CASSANDRA can be used to generate robust decisions on the execution of CAMs in an automated way.},

keywords = {Artificial Intelligence, Collision Avoidance Manoeuvre, Conjunction Assessment, Robust Decision-making, Space Traffic Management},

pubstate = {published},

tppubtype = {inproceedings}

}