PRISM-VO introduces photometric plenoptic bundle adjustment for drift-resilient, metric-scale visual odometry from a single focused plenoptic camera.
Transactions on Robotics (T-RO)37(6), 1874–1890 (2021).https://doi
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SA-LIVO uses eigendecomposition of the joint information matrix with linear-clamp soft gates per eigendirection for efficient degeneracy-aware LiDAR-inertial-visual odometry.
Pose graph optimization is recast as damped Riemannian dynamics on Lie groups, enabling a fully distributed algorithm with a semi-implicit integrator that converges under both synchronous and asynchronous communication.
TACO is a robust optimization framework for pose graph SLAM that combines online consistency testing with periodic sanitization using switchable constraints, showing high success rates on datasets with up to 50% outliers.
EgoAERO reconstructs contact-consistent hand-object trajectories from single egocentric RGB-D videos without object assets via asset-free tracking and adaptive optimization, then trains robot policies with two-stage residual learning, achieving performance close to CAD-based methods.
A LiDAR-inertial odometry pipeline using on-manifold ellipsoidal set-membership filtering to output feasible sets as deterministic protection levels under unknown-but-bounded point-cloud noise.
Pocket-SLAM introduces rendering-area-aware pruning for 3DGS-SLAM, claiming over 60% memory reduction and 2x FPS gain on EuRoC and KITTI while keeping localization and mapping accuracy.
A fully discrete strain-based model for continuum robot dynamics via Lie group variational integrators, combined with an EKF-based observer for states and disturbances, validated on hardware.
The paper introduces and experimentally verifies PEBRE, an open-hardware compute and perception module for the Pepper robot that integrates a Jetson Orin Nano and additional sensors to improve performance.
A robotics framework combines VLMs and kernel regression for online learning from embodiment-specific disturbances to enable better adaptation in unstructured environments.
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Distributed Pose Graph Optimization via Continuous Riemannian Dynamics
Pose graph optimization is recast as damped Riemannian dynamics on Lie groups, enabling a fully distributed algorithm with a semi-implicit integrator that converges under both synchronous and asynchronous communication.