News

Traditional visual-inertial Simultaneous Localization and Mapping (SLAM) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment ...
During robotic disaster relief missions, state estimation still faces significant challenges, especially when GNSS is denied or sensor perception undergoes degradation. In this letter, we introduce a ...
Visual-Inertial Odometry (VIO) combines Visual-SLAM and IMU, realizing a more robust local pose estimation than either of the two. In this paper, the invariant optimization approach has been applied ...
In this paper, we introduce Collaborative SLAM using Visual Odometry and Ranges (CoVOR-SLAM) to address these challenges. CoVOR-SLAM significantly reduces both the amount of data transmitted between ...
Simultaneous Localization and Mapping (SLAM) has become a critical technology for intelligent transportation systems and autonomous robots and is widely used in autonomous driving. However, ...
With the rapid development of agricultural intelligence, the application of intelligent agricultural robots in orchard management has been widely concerned. However, the complex environment in apple ...
Joint optimization of poses and features has been extensively studied and demonstrated to yield more accurate results in feature-based SLAM problems. However, research on jointly optimizing poses and ...