76 citations · 131 across the 9 of their papers we have counts for
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Does Robust VIO Need More Learning? Geometry-Verified Visual Measurements under Distribution Shift
Yangyang Ning, Shu Liang, Quanbo Ge +3
Learning is increasingly introduced into visual-inertial odometry (VIO), ranging from learned feature front-ends to learning-dominant motion and geometry estimation. However, learn…
GNIO: Gated Neural Inertial Odometry
Dapeng Feng, Yizhen Yin, Zhiqiang Chen +2
Inertial navigation using low-cost MEMS sensors is plagued by rapid drift due to sensor noise and bias instability. While recent data-driven approaches have made significant stride…
PUL-SLAM: Path-Uncertainty Co-Optimization with Lightweight Stagnation Detection for Efficient Robotic Exploration
Yizhen Yin, Dapeng Feng, Hongbo Chen +1
Existing Active SLAM methodologies face issues such as slow exploration speed and suboptimal paths. To address these limitations, we propose a hybrid framework combining a Path-Unc…
MA-SLAM: Active SLAM in Large-Scale Unknown Environment using Map Aware Deep Reinforcement Learning
Yizhen Yin, Yuhua Qi, Dapeng Feng +4
Active Simultaneous Localization and Mapping (Active SLAM) involves the strategic planning and precise control of a robotic system's movement in order to construct a highly accurat…
Heterogeneous LiDAR Dataset for Benchmarking Robust Localization in Diverse Degenerate Scenarios
Zhiqiang Chen, Yuhua Qi, Dapeng Feng +6
The ability to estimate pose and generate maps using 3D LiDAR significantly enhances robotic system autonomy. However, existing open-source datasets lack representation of geometri…
RELEAD: Resilient Localization with Enhanced LiDAR Odometry in Adverse Environments
Zhiqiang Chen, Hongbo Chen, Yuhua Qi +5
LiDAR-based localization is valuable for applications like mining surveys and underground facility maintenance. However, existing methods can struggle when dealing with uninformati…