11 papers
DINS-IO: Learned Inertial Odometry via Differentiable INS Consistency
Hao Qiao, Yan Wang, Jian Kuang +1
The training of learned inertial odometry depends on dense, high-precision position ground truth from motion capture, visual-inertial odometry or SLAM, which is costly and hard to…
ViBA: Implicit Bundle Adjustment with Geometric and Temporal Consistency for Robust Visual Matching
Xiaoji Niu, Yuqing Wang, Yan Wang +2
Most existing image keypoint detection and description methods rely on datasets with accurate pose and depth annotations, limiting scalability and generalization, and often degradi…
PA-LVIO: Real-Time LiDAR-Visual-Inertial Odometry and Mapping with Pose-Only Bundle Adjustment
Hailiang Tang, Tisheng Zhang, Liqiang Wang +3
Real-time LiDAR-visual-inertial odometry and mapping is crucial for navigation and planning tasks in intelligent transportation systems. This study presents a pose-only bundle adju…
MoE-Based Learned Inertial Odometry for Bicycle Localization
Hao Qiao, Yan Wang, Shuo Yang +3
GNSS suffers from multipath errors in urban canyons, making reliable bicycle localization difficult. Hand-crafted inertial alternatives, such as cycling dead reckoning and nonholon…
i2Nav-Robot: A Large-Scale Indoor-Outdoor Robot Dataset for Multi-Sensor Fusion Navigation
Hailiang Tang, Tisheng Zhang, Liqiang Wang +9
Accurate and reliable navigation is crucial for autonomous unmanned ground vehicles (UGVs). However, current UGV datasets fall short in meeting the demands for advancing navigation…
DogLegs: Robust Proprioceptive State Estimation for Legged Robots Using Multiple Leg-Mounted IMUs
Yibin Wu, Jian Kuang, Shahram Khorshidi +4
Robust and accurate proprioceptive state estimation of the main body is crucial for legged robots to execute tasks in extreme environments where exteroceptive sensors, such as LiDA…