An IterIEKF algorithm for quadruped odometry, relying on proprioceptive kinematic constraints, outperforms vanilla IEKF and SO(3) Kalman filters in accuracy and consistency on simulations and real datasets.
Grandtour: A legged robotics dataset in the wild for multi-modal perception and state estimation
3 Pith papers cite this work. Polarity classification is still indexing.
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ViLiNT improves goal-conditioned navigation success rates by 166% on average over vision-only baselines across simulations and real rover tests by combining multimodal sensing with embodiment-conditioned diffusion trajectories and clearance scoring.
Benchmark of MUSE, IEKF, and IS on CYN-1 sequence shows similar RPEs, lower ATE for IEKF and IS, and accuracy-latency trade-offs with open-source evaluation code.
citing papers explorer
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Iterated Invariant EKF for Quadruped Robot Odometry
An IterIEKF algorithm for quadruped odometry, relying on proprioceptive kinematic constraints, outperforms vanilla IEKF and SO(3) Kalman filters in accuracy and consistency on simulations and real datasets.
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Multimodal embodiment-aware navigation transformer
ViLiNT improves goal-conditioned navigation success rates by 166% on average over vision-only baselines across simulations and real rover tests by combining multimodal sensing with embodiment-conditioned diffusion trajectories and clearance scoring.
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A Proprioceptive-Only Benchmark for Quadruped State Estimation: ATE, RPE, and Runtime Trade-offs Between Filters and Smoothers
Benchmark of MUSE, IEKF, and IS on CYN-1 sequence shows similar RPEs, lower ATE for IEKF and IS, and accuracy-latency trade-offs with open-source evaluation code.