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Published June 1, 2021 | Accepted Version
Journal Article Open

Decentralized formation pose estimation for spacecraft swarms

Abstract

For spacecraft swarms, the multi-agent localization algorithm must scale well with the number of spacecraft and adapt to time-varying communication and relative sensing networks. In this paper, we present a decentralized, scalable algorithm for swarm localization, called the Decentralized Pose Estimation (DPE) algorithm. The DPE considers both communication and relative sensing graphs and defines an observable local formation. Each spacecraft jointly localizes its local subset of spacecraft using direct and communicated measurements. Since the algorithm is local, the algorithm complexity does not grow with the number of spacecraft in the swarm. As part of the DPE, we present the Swarm Reference Frame Estimation (SRFE) algorithm, a distributed consensus algorithm to co-estimate a common Local-Vertical, Local-Horizontal (LVLH) frame. The DPE combined with the SRFE provides a scalable, fully-decentralized navigation solution that can be used for swarm control and motion planning. Numerical simulations and experiments using Caltech's robotic spacecraft simulators are presented to validate the effectiveness and scalability of the DPE algorithm.

Additional Information

© 2020 Published by Elsevier Ltd on behalf of COSPAR. Accepted 11 June 2020, Available online 26 June 2020. This research was supported in part by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The work of Kai Matsuka was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE 1745301. We also would like to thank Alexei Harvard for his help on camera calibration as well as to Jennifer Sun and Amir Rahmani for their technical support. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Created:
August 22, 2023
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October 20, 2023