LiDAR data augmentation by interpolation on spherical range image

LiDAR sensors are used for mapping tasks, LiDAR odometry or 3D environment reconstruction. Several of them count with a high number of vertical layers, which increase their price and prevents research groups from carrying out experiments and scientific advances. In this paper, we propose a method for augmenting point cloud data by bilinear interpolation in a Spherical Range Image. Our method improves others on the state-of-the-art by means of standard deviation filtering of the newly generated layers. The system operates at a frequency greater than 10 Hz for data interpolation up to 20 times. In addition, we present two applications for our approach such as LiDAR odometry and LiDAR-Camera fusion, obtaining better results than others that do not apply data augmentation. Finally we make available to the scientific community a package development on ROS (Robot Operating System). The code is available at https://github.com/EPVelasco/lidar-camera-fusion

I. Introduction and related works

Light Detection And Ranging (LiDAR) technology has been used in recent years in the field of robotics for autonomous driving. Its characteristics of generating point clouds using optical waves have the potential to achieve better accuracy in detecting at indoor or outdoor environments [1], [2]. One of the mostly used sensors of this kind in the autonomous robotics are those having a 360-degree Field Of View (FOV) [3] –[5]. They are marketed depending on the resolution and number of layers on the vertical axis. Generally, a higher number of layers represent a higher price. That is why several works that include them are performed with less-layer sensors [6] –[9].