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arXiv Robotics — research abstracts· Shuyue Li, Miguel L\'opez-Ben\'itez, Eng Gee Lim, Fei Ma, Qian Dong, Mengze Cao, Limin Yu, Xiaohui Qin·· 16 hours agoSignalEditorial score75

Compressed delayed-information projection for underwater navigation under acoustic measurement latency

Compressed delayed-information projection for underwater navigation under acoustic measurement latency

Summary

This paper introduces Compressed Delayed-Information Projection (CDIP), a causal delayed-update method implemented within a 15-dimensional error-state Kalman filter.

Editorial context

The study evaluates a causal delayed-update method in an underwater navigation context using simulation data, reporting specific error metrics and computational savings under defined latency conditions.

Source: arXiv Robotics — research abstracts · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Environment
SimulationOpen source S3

Reported numbers

  • mean trajectory-position root-mean-square error

    0.456

    View original evidence
    ) snapshots and maintains current-to-snapshot cross-covariances, projecting delayed corrections without repeated full-from-start filtering. In 154 paired simulation recordings with synthetic horizontal-position fixes delayed by 1.5~s, CDIP reduced mean trajectory-position root-mean-square error (RMSE) from 1.062~m for a reception-time Baseline to 0.456~m (57.1\%). Its mean RMSE approached that of full-from-start Repl
    Open source S3
  • mean trajectory-position root-mean-square error

    1.062

    View original evidence
    ) snapshots and maintains current-to-snapshot cross-covariances, projecting delayed corrections without repeated full-from-start filtering. In 154 paired simulation recordings with synthetic horizontal-position fixes delayed by 1.5~s, CDIP reduced mean trajectory-position root-mean-square error (RMSE) from 1.062~m for a reception-time Baseline to 0.456~m (57.1\%). Its mean RMSE approached that of full-from-start Repl
    Open source S3
  • number of paired simulation recordings

    154

    View original evidence
    ) snapshots and maintains current-to-snapshot cross-covariances, projecting delayed corrections without repeated full-from-start filtering. In 154 paired simulation recordings with synthetic horizontal-position fixes delayed by 1.5~s, CDIP reduced mean trajectory-position root-mean-square error (RMSE) from 1.062~m for a reception-time Baseline to 0.456~m (57.1\%). Its mean RMSE approached that of full-from-start Repl
    Open source S3
  • delay duration for synthetic horizontal-position fixes

    1.5

    View original evidence
    ) snapshots and maintains current-to-snapshot cross-covariances, projecting delayed corrections without repeated full-from-start filtering. In 154 paired simulation recordings with synthetic horizontal-position fixes delayed by 1.5~s, CDIP reduced mean trajectory-position root-mean-square error (RMSE) from 1.062~m for a reception-time Baseline to 0.456~m (57.1\%). Its mean RMSE approached that of full-from-start Repl
    Open source S3
  • number of nonlinear synthetic assessment trials

    256

    Reported trials

    View original evidence
    ay (0.451~m), with 99.2\% lower mean core-loop time per processed IMU step for the tested implementations. A six-delay sweep, scheduled permanent-loss outages of 50--300~s, and packet-erasure tests further characterized sensitivity to measurement timing and availability. A separate 256-trial nonlinear synthetic assessment identified departures from the prespecified calibration criterion for CDIP and two fully augment
    Open source S4
  • paper: not_reported
Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

) snapshots and maintains current-to-snapshot cross-covariances, projecting delayed corrections without repeated full-from-start filtering. In 154 paired simulation recordings with synthetic horizontal-position fixes delayed by 1.5~s, CDIP reduced mean trajectory-position root-mean-square error (RMSE) from 1.062~m for a reception-time Baseline to 0.456~m (57.1\%). Its mean RMSE approached that of full-from-start Repl

Open source S3

ay (0.451~m), with 99.2\% lower mean core-loop time per processed IMU step for the tested implementations. A six-delay sweep, scheduled permanent-loss outages of 50--300~s, and packet-erasure tests further characterized sensitivity to measurement timing and availability. A separate 256-trial nonlinear synthetic assessment identified departures from the prespecified calibration criterion for CDIP and two fully augment

Open source S4

Source:arXiv Robotics — research abstracts · arxiv.org

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