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OKVIS2: Realtime Scalable Visual-Inertial SLAM with Loop Closure

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arxiv 2202.09199 v2 pith:6ANHO4PB submitted 2022-02-18 eess.IV

Stefan Leutenegger This is my paper · ORCID
classification eess.IV
keywords observationsedgespose-graphrealtimevi-slamvisual-inertialaccurateachieve
verification ladder T0 review T1 audit T2 compute T3 formal
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Robust and accurate state estimation remains a challenge in robotics, Augmented, and Virtual Reality (AR/VR), even as Visual-Inertial Simultaneous Localisation and Mapping (VI-SLAM) getting commoditised. Here, a full VI-SLAM system is introduced that particularly addresses challenges around long as well as repeated loop-closures. A series of experiments reveals that it achieves and in part outperforms what state-of-the-art open-source systems achieve. At the core of the algorithm sits the creation of pose-graph edges through marginalisation of common observations, which can fluidly be turned back into landmarks and observations upon loop-closure. The scheme contains a realtime estimator optimising a bounded-size factor graph consisting of observations, IMU pre-integral error terms, and pose-graph edges -- and it allows for optimisation of larger loops re-using the same factor-graph asynchronously when needed.

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Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation

    cs.RO 2026-02 conditional novelty 7.0 of 10

    GrandTour releases 49 multi-modal legged-robot missions (>10 km, >5 h) with LiDAR, camera, IMU, depth, proprioception, and mm-level RTK-GNSS/total-station ground truth, plus a 52-method state-estimation benchmark.

  2. VidMap: Exploiting Temporal Structure for Video-Based Structure-from-Motion

    cs.CV 2026-07 accept novelty 6.0 of 10

    VidMap recovers more accurate metric poses and calibration from long unconstrained videos than SOTA SLAM and SfM by treating temporal order as first-class and injecting metric depth into global optimization.

  3. HumanHalo -- Safe and Efficient 3D Navigation Among Humans via Minimally Conservative MPC

    cs.RO 2025-10 conditional novelty 6.0 of 10

    The paper contributes a linear MPC safety constraint that, for the first control input alone, prevents the drone's future reachable set from ever being fully inside a human's reachable set, avoiding inevitable collisions.

  4. GSFix3D: Diffusion-Guided Repair of Novel Views in Gaussian Splatting

    cs.CV 2025-08 conditional novelty 6.0 of 10

    A per-scene fine-tuned latent diffusion model with dual mesh-3DGS conditioning and random mask augmentation improves novel-view repair in Gaussian Splatting, outperforming DIFIX baselines on ScanNet++ and Replica.

  5. Does Robust VIO Need More Learning? Geometry-Verified Visual Measurements under Distribution Shift

    cs.RO 2026-07 conditional novelty 5.0 of 10

    Restricting learning to stereo correspondence and uncertainty, with geometric verification and covariance weighting in an explicit VIO backend, improves OOD trajectory accuracy and success rate over classical and lear...

  6. SMF-VO: Direct Ego-Motion Estimation via Sparse Motion Fields

    cs.RO 2025-11 conditional novelty 4.0 of 10

    SMF-VO estimates a camera's velocity directly from sparse optical flow with a ray-based motion-field equation, reporting >100 FPS on a Raspberry Pi with competitive visual-odometry accuracy.

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