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Robust Entry Vehicle Guidance with Sampling-Based Invariant Funnels

2020/11/04 by Derollez, Remy, Cleac'h, Simon Le, Manchester, Zachary
#FOS: Computer and information sciences #Robotics (cs.RO)

paper · doi:10.48550/arxiv.2011.02441

Abstract

Managing uncertainty is a fundamental and critical issue in spacecraft entry guidance. This paper presents a novel approach for uncertainty propagation during entry, descent and landing that relies on a new sum-of-squares robust verification technique. Unlike risk-based and probabilistic approaches, our technique does not rely on any probabilistic assumptions. It uses a set-based description to bound uncertainties and disturbances like vehicle and atmospheric parameters and winds. The approach leverages a recently developed sampling-based version of sum-of-squares programming to compute regions of finite time invariance, commonly referred to as "invariant funnels". We apply this approach to a three-degree-of-freedom entry vehicle model and test it using a Mars Science Laboratory reference trajectory. We compute tight approximations of robust invariant funnels that are guaranteed to reach a goal region with increased landing accuracy while respecting realistic thermal constraints.

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