LiDAR based Autonomous Navigation for USV Pipeline Inspection

Abstract

In general, the use of transportation is one of the techniques that allows anything to move faster without consuming a lot of energy. These also apply to the pipeline-based transfer of liquids, gases, and other substances. Therefore, these pipelines need to be inspected to keep them free of corrosion and in good shape. However, this pipeline is occasionally located in a location that is challenging for humans to access, such as located above the water surface, then Heron Unmanned Surface Vehicle (USV) is proposed to overcome the aforementioned problems. This study discusses the development of the Heron unmanned surface vehicle's (USV) autonomous SLAM navigation, path planning, and collision avoidance system. Additional sensors, such as a Velodyne 3D VLP16 lidar sensor and an Axis pan-tilt-zoom (PTZ) camera, will be mounted to the Heron USV to enhance the autonomous navigation capabilities of the Heron USV. The Robot Operating System (ROS) navigation stack is used to provide the framework for the hardware and software of the robot to develop the Simultaneous Localization and Mapping (SLAM) based autonomous navigation and path planning algorithm. The lidar sensor data has been analyzed, showing that the lidar sensor can identify the surrounding environment and objects around the USV. The results show that the suggested USV can navigate autonomously in a water environment, including path planning, and can avoid obstacles. Due to the data collected from the lidar sensor, the USV can also generate a map for the unknown area while navigating around the simulated environment, which aids in visualizing the current state in the environment and can be used in pipeline inspection.