Online feedback motion planning for spacecraft obstacle avoidance using positively invariant sets

Dengwei Gao, Jianjun Luo, Weihua Ma, Brendan Englot

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

This paper investigates a novel reliable feedback motion planning algorithm for steering a spacecraft to the desired position while satisfying dynamics and environmental constraints, such as actuator constraints, unexpected state constraints, bounded disturbances, etc. The proposed algorithm, termed safeRRT∗, applies positively invariant (PI) set transitions to an online sampling approach based on the asymptotically optimal rapidly-exploring random tree (RRT∗). A time-varying safe corridor is generated which consists of a sequence of PI sets under the instantaneous constraints. A spacecraft is guaranteed to remain within the corridor when the feedback controllers corresponding to the PI set transitions are executed. Simulations of the spacecraft avoiding obstacles validate the feasibility and effectiveness of the proposed safeRRT∗ algorithm.

Original languageEnglish
Pages (from-to)2424-2434
Number of pages11
JournalAdvances in Space Research
Volume65
Issue number10
DOIs
StatePublished - 15 May 2020

Keywords

  • Asymptotic optimality
  • Motion planning
  • Online replanning
  • Positively invariant set

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