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News/Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation
arxiv
PublishedMay 6, 2026 at 4:00 AM
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Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2601.18569v2 Announce Type: replace-cross Abstract: In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a major source of estimation error: when slip occurs, kinematic measurements violate the no-slip assum

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Discussion
Mentioned models
02
  • 01
    Attention-Based Neural-Augmented Kalman Filter (AttenNKF)
  • 02
    Invariant Extended Kalman Filter (InEKF)
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arxiv
Read original ↗All from arxiv →
Tags
04
#robotics#state-estimation#legged-robots#kalman-filter

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Mentioned models
02
  • 01
    Attention-Based Neural-Augmented Kalman Filter (AttenNKF)
  • 02
    Invariant Extended Kalman Filter (InEKF)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#robotics#state-estimation#legged-robots#kalman-filter

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arxivMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation1harxivCounterfactual Model Testing Under Distribution Shift1harxivCentralized Critics for N-Agent Ad Hoc Teamwork1harxivWhere and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning1h
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