Spacecraft Relative Motion Planning Using Chained Chance-Constrained Admissible Sets

TL;DR

This paper develops a probabilistic motion planning method for spacecraft that ensures safety constraints are met with high probability, even with noisy measurements and stochastic disturbances, using chained chance-constrained admissible sets.

Contribution

It extends previous invariant set methods to stochastic output feedback scenarios with non-convex constraints, enabling safer spacecraft proximity operations.

Findings

Handles non-convex exclusion zones.

Guarantees constraint satisfaction with specified probability.

Applicable to noisy measurement and stochastic disturbances.

Abstract

With the increasing interest in proximity and docking operations, there is a growing interest in spacecraft relative motion control. This paper extends a previously proposed constrained relative motion approach based on chained positively invariant sets to the case where the spacecraft dynamics are controlled using output feedback on noisy measurements and are subject to stochastic disturbances. It is shown that non-convex polyhedral exclusion zone constraints can be handled. The methodology consists of a virtual net of static equilibria nodes in the Clohessy-Wiltshire-Hill frame. Connectivity between nodes is determined through the use of chance-constrained admissible sets, guaranteeing that constraints are met with a specified probability.