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This paper considered an object detection system based on 3D LiDAR Sensor and Simultaneous Localization and Mapping (SLAM) to complete the navigation applications of mobile robots. A 3D-based SLAM with lightweight and ground-optimized Lidar odometry and mapping (LeGO-LOAM) appropriately generated the environmental maps. SLAM is a tool used to obtain information from the environment, allowing mobile robots to know their location. Indoor environment data is immedicably created while SLAM is processing the information. The dynamic object detection algorithm depends on the available information to realize the external morphology and circle the bounding box of moving objects. Therefore, a wheeled mobile robot (WMR) was employed to dynamically trace the object’s movement direction. Finally, This study found that the quantum genetic algorithm (QGA) is more efficient in generating a shorter path than the particle swarm optimization, and a dynamic window approach (DWA) is immediately detected as a dynamic obstacle. Therefore, WMR obtains enough object, obstacle, and routing information to effectively and safely reach the destination through the Move_base software package in Robot Operating System.

3D lidar SLAM-based systems in object detection and navigation applications