7 papers
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…
CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAM
Dapeng Feng, Zhiqiang Chen, Yizhen Yin +3
Simultaneous Localization and Mapping (SLAM) is pivotal in robotics, with photorealistic scene reconstruction emerging as a key challenge. To address this, we introduce Computation…
S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM
Dapeng Feng, Yuhua Qi, Shipeng Zhong +5
The burgeoning demand for collaborative robotic systems to execute complex tasks collectively has intensified the research community's focus on advancing simultaneous localization…