Abstract

Accumulating space debris edges the space domain ever closer to cascading Kessler syndrome, a chain reaction of debris generation that could dramatically inhibit the practical use of space. Meanwhile, a growing number of retired satellites, particularly in higher orbits like geostationary orbit, remain nearly functional except for minor but critical malfunctions or fuel depletion. Servicing these ailing satellites and cleaning up “high-value” space debris remains a formidable challenge, but active interception of these targets with autonomous repair and deorbit spacecraft is inching closer toward reality as shown through a variety of rendezvous demonstration missions. However, some practical challenges are still unsolved and undemonstrated. Devoid of station-keeping ability, space debris and fuel-depleted satellites often enter uncontrolled tumbles on-orbit. In order to perform on-orbit servicing or active debris removal, docking spacecraft (the “Chaser”) must account for the tumbling motion of these targets (the “Target”), which is oftentimes not known a priori. Accounting for the tumbling dynamics of the Target, the Chaser spacecraft must have an algorithmic approach to identifying the state of the Target’s tumble, then use this information to produce useful motion planning and control. Furthermore, careful consideration of the inherent uncertainty of any maneuvers must be accounted for in order to provide guarantees on system performance. This study proposes the complete pipeline of rendezvous with such a Target, starting from a standoff estimation point to a mating point fixed in the rotating Target’s body frame. A novel visual estimation algorithm is applied using a 3D time-of-flight camera to perform remote standoff estimation of the Target’s rotational state and its principal axes of rotation. A novel motion planning algorithm is employed, making use of offline simulation of potential Target tumble types to produce a look-up table that is parsed on-orbit using the estimation data. This nonlinear programming-based algorithm accounts for known Target geometry and important practical constraints such as field of view requirements, producing a motion plan in the Target’s rotating body frame. Meanwhile, an uncertainty characterization method is demonstrated which propagates uncertainty in the Target’s tumble uncertainty to provide disturbance bounds on the motion plan’s reference trajectory in the inertial frame. Finally, this uncertainty bound is provided to a robust tube model predictive controller, which provides tube-based robustness guarantees on the system’s ability to follow the reference trajectory translationally. The combination and interfaces of these methods are shown, and some of the practical implications of their use on a planned demonstration on NASA’s Astrobee free-flyer are additionally discussed. Simulation results of each of the components individually and in a complete case study example of the full pipeline are presented as the study prepares to move toward demonstration on the International Space Station.

Highlights

  • The Chaser coordinator orchestrates all parts of the autonomy pipeline and activates each step based on timing parameters and completion status

  • The framework and algorithms proposed in this study are a significant step toward autonomous rendezvous with tumbling Targets, uniting multiple key algorithmic components of the autonomy pipeline

  • Planned International Space Station (ISS) tests in mid2021 on the Astrobee platform will provide extensive experimental validation of this study, which has been shown algorithmically defined here and demonstrated in a detailed simulation environment that directly transfers to the Astrobee hardware

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Summary

INTRODUCTION

In a variety of sub-fields of space robotics, including on-orbit servicing and repair, active debris removal, and on-orbit assembly, the ability to dock with arbitrary tumbling objects given the limited initial knowledge of the Target object is a key capability (Flores-Abad et al, 2014). The need remains for a complete autonomy pipeline for such a maneuver that is robust to the most significant uncertainty sources of autonomous docking with tumbling Targets and that can operate with automatic visual estimation and motion planning components This study details such a framework that can account for some of the key uncertainty sources of tumbling rendezvous; the unknown Target tumble state. The remainder of this article is formulated as follows: Section 2 outlines the autonomous rendezvous problem; Section 3 details the varied methods needed to form the full autonomy pipeline and how these segments interact; Section 4 presents results of individual components as well as a case study example of the full pipeline algorithm in a detailed simulation environment; and Section 5 includes a discussion of the proposed pipeline and plans for integration and future experimental testing

PROBLEM FORMULATION
Representative Satellite System of Interest
System Dynamics
Chaser Motion Constraints
Constraints for the System of Interest
Uncertainty Sources
The Autonomy Pipeline
Relative Navigation and Target Characterization
Estimation of Angular Velocity and Target Principal Axes
Δtij Log
Chaser Motion Planning
Uncertainty Bound Definition
Robust Tube Model Predictive Control
RESULTS
State and Principal Axes Estimation Performance
Chaser Motion Planning Performance
Uncertainty Bound and Robust Tube MPC Performance
The Full Pipeline: A Case Study Result
CONCLUSION
DATA AVAILABILITY STATEMENT
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