A robust Bayesian agent for optimal collision avoidance manoeuvre planning

C. Greco, L. Sánchez, M. Manzi, M. Vasile

Research output: Contribution to conferencePaperpeer-review

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This paper addresses the problem of automatically allocating Collision Avoidance Manoeuvres under uncertainty by a robust Bayesian framework. This framework allows propagating the objects' uncertainty, predicting collisions, allocating manoeuvres, updating the state estimation with Bayesian inference, and redefining the manoeuvres, accounting at all steps for aleatory and epistemic uncertainty.
The Bayesian framework combines a robust particle filter for state estimation and uncertainty propagation, an intelligent agent for automatically classifying risk events and allocating avoidance manoeuvres, and a Collision Avoidance Manoeuvre optimiser for obtaining the optimal manoeuvre.
A test case is included to show the operation of the system. Two scenarios are presented: a collision and a near-miss conjunction.
Original languageEnglish
Number of pages11
Publication statusPublished - 23 Apr 2021
Event8th European Conference on Space Debris - ESA/ESOC, Darmstadt, Germany
Duration: 20 Apr 202123 Apr 2021


Conference8th European Conference on Space Debris
Internet address


  • robust Bayesian estimation
  • intelligent agent
  • collision avoidance optimisation
  • epistemic uncertainty


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