3 accepted papers
We propose a graph SLAM algorithm for sparse range sensing that incorporates a soft Manhattan world utilizing landmark-landmark constraints. Sparse range sensing is necessary for tiny robots that do not have the luxury of using heavy and expensive sensors. Existing SLAM methods dealing with sparse r…
We present a novel calibration method between single-point LiDAR and camera sensors utilizing an easy-to-build customized calibration board satisfying the Manhattan world (MW). Previous methods for LiDAR-camera (LC) calibration focus on line and plane correspondences. However, they require dense 3D
We propose a novel graph SLAM algorithm for sparse range sensing that incorporates a soft Manhattan world utilizing landmark-landmark constraints. Sparse range sensing is necessary for tiny robots that do not have the luxury of using heavy and expensive sensors. Existing SLAM methods dealing with sp