Lidar Point Cloud Compression, Processing and Learning for Autonomous Driving

As technology advances, cities are getting smarter. Smart mobility is the key element in smart and Autonomous Driving (AV) an essential part of mobility. However, vulnerability unmanned vehicles can also affect value life human safety. In this paper, we provide a comprehensive analysis 3D Point-Cloud (3DPC) processing learning terms development, advancement, performance for AV system. 3DPC has recently attracted growing interest due to its extensive applications, such as autonomous driving, computer vision, robotics. Light Detection Ranging Sensors (LiDAR) one most significant sensors AV, which collects that accurately capture outer surfaces scenes objects. Learning tools creating maps, perceptions, localization devices AV. The intention behind practical be considered modules create, locate, perceive maps goal study know “what been tested system so far what necessary make it safer more system.” We insights into open problems required resolved future.