Optical Flow-Based Lidar Odometry

Abstract

In this study, data obtained from a 360-degree (or 2D) Light Detection and Ranging sensor, which is commonly used for Simultaneous Localization and Mapping, were converted into an image/frame matrix to apply optical flow methods. Key features on the resulting image matrix were identified as corners using the Shi-Tomasi method. The positional changes of these key features during each complete measurement cycle of the LiDAR sensor were calculated using the Lucas-Kanade method, an optical flow technique. These positional changes were analyzed to estimate the vehicle’s displacement within the environment. The developed method was tested in a simulation environment with different object densities, moving linearly at different speeds, both constant and variable.