LiDAR based system for tracking loader crane operator

Abstract

Nowadays, particularly in the IoT, industry 4.0, smart devices, intelligent robots and autonomous vehicles, the segmentation and analysis of the environment using 3D data (point clouds) is a current and relevant research topic. The reducing prices of depth sensors based on light detection and ranging (LIDAR), time of flight (ToF), radio detection and ranging (RADAR) technologies and high computing power, facilitate the development of intelligent systems. In this work real-time LiDAR based system for tracking loader crane operator has been presented. Developed system uses a Velodyne VLP-16 LiDAR to detect and track loader crane operator and is fully integrated with open-source ROS (Robot Operating System). This solution will help to determine whether the operator is in the crane working zone, which will increase his safety. The work presents the main assumptions of the system, subsequent stages of point clouds processing and used algorithms. Detection and tracking algorithms performance was evaluated based on real data acquired under different conditions, and the results were compared to similar solutions found in the literature. The results of conducted test were presented. Furthermore, in this article, we discussed other methods used to detect and track humans in real time, described Velodyne VLP-16 scanner, robot operating system and data processing methods.