Multi-LiDAR SLAM and Intelligent Navigation for Autonomous Logistic Robots in ROS2 Environments

Leonard Priyatna Rusli; Michael Jonathan; Rusman Rusyadi; Leonard Priyatna Rusli; Michael Jonathan; Rusman Rusyadi

doi:10.55981/j.mev.2026.1187

Multi-LiDAR SLAM and Intelligent Navigation for Autonomous Logistic Robots in ROS2 Environments

Leonard Priyatna Rusli, Michael Jonathan, Rusman Rusyadi

Abstract

The mobilization of materials within industrial environments is a fundamental yet repetitive task. While Automated Guided Vehicles (AGVs) are widely used for automation, their reliance on predefined paths limits their adaptability. Autonomous Mobile Robots (AMRs) provide a more flexible solution by employing Simultaneous Localization and Mapping (SLAM), autonomous navigation, and obstacle avoidance. This study presents the development of an indoor AMR based on Robot Operating System 2 (ROS2), integrating multiple Light Detection and Ranging (LiDAR) sensors for SLAM, an RS-485 Modbus-based brushless DC (BLDC) motor driver for actuation and wheel odometry, ultrasonic sensors for safety, an Inertial Measurement Unit (IMU) for odometry, and a network of calling stations as the primary user interface. Experimental validation confirms successful LiDAR data fusion, with the RS-485 Modbus-based motor driver achieving a motion control error of 0.36% and a speed retrieval error of 0.43%. Furthermore, the AMR effectively receives and executes commands from calling stations via the Message Queuing Telemetry Transport (MQTT) protocol. The system demonstrates dynamic point-to-point navigation with a positional repeatability of 10.3 cm. These findings contribute to the advancement of autonomous material handling, enhancing efficiency and reducing human intervention in industrial logistics

10.55981/j.mev.2026.1187

Keywords

Autonomous Mobile Robot; Robot Operating System 2; RS-485 Modbus; MQTT; Multi LiDARs SLAM in ROS2

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References

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