SA-LIVO uses eigendecomposition of the joint information matrix with linear-clamp soft gates per eigendirection for efficient degeneracy-aware LiDAR-inertial-visual odometry.
Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam.IEEE Transactions on Robotics2021; 37(6): 1874–1890
9 Pith papers cite this work. Polarity classification is still indexing.
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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.
citing papers explorer
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SA-LIVO: Efficient LiDAR-Inertial-Visual Odometry with Subspace-Aware Degeneracy Handling
SA-LIVO uses eigendecomposition of the joint information matrix with linear-clamp soft gates per eigendirection for efficient degeneracy-aware LiDAR-inertial-visual odometry.
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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.
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TACO: A Test and Check Framework for Robust Pose Graph Optimization
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.
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EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets
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.
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Safety-Critical LiDAR-Inertial Odometry with On-Manifold Deterministic Protection Level
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.
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Pocket-SLAM: Rendering-Area-Aware Pruning for Memory-Efficient 3DGS-SLAM
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.
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Discrete Geometric Modeling and Extended State Estimation of Continuum Robots
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.
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PEBRE: An Open-Hardware Compute and Perception Add-On for the Pepper Robot
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.
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Don't Fool Me Twice: Adapting to Adversity in the Wild with Experience-Driven Reasoning
A robotics framework combines VLMs and kernel regression for online learning from embodiment-specific disturbances to enable better adaptation in unstructured environments.