In this paper, we present a robust, real-time LOAM algorithm for LiDARs with small FoV and irregular samplings. By taking effort on both front-end and back-end, we address several fundamental challenges arising from such LiDARs, and achieve better performance in both precision and efficiency compared to existing baselines.
This investigation focuses on the performance assessment of a low-cost automotive LIDAR, the Livox Mid-40 series. The work aims to examine the qualities of the sensor in terms of ranging, repeatability and accuracy.
This paper reviews the current status of the light and miniature UAV-borne LiDAR in China and other contries, then typical applications in related fields are listed. Finally, some future perspectives are presented.
In this paper, an autonomous system design is proposed for dam ground surveillance robots, which includes general solution, electromechanical layout, sensors scheme, and navigation method.
We present a cost-friendly vehicle research platform and a robust implementation of SLAM. Our SLAM algorithm fuses visual stereo image and 2D light detection and ranging (Lidar) data and uses loop closure for accurate odometry estimation.
We propose a robotic lidar sensor based on incommensurable scanning that allows straightforward mass production and adoption in autonomous robots. Some unique features are additionally permitted by this incommensurable scanning.