Design and Implementation of an Integrated Control System for Omnidirectional Mobile Robots in Industrial Logistics

The integration of intelligent robots in industrial production processes has the potential to significantly enhance efficiency and reduce human adversity. However, for such robots to effectively operate within human environments, it is critical that they possess an adequate understanding of their su...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2023-03, Vol.23 (6), p.3184
Main Authors: Neaz, Ahmed, Lee, Sunyeop, Nam, Kanghyun
Format: Article
Language:English
Subjects:
Autonomous navigation
autonomous robot 2
Collaboration
Computer architecture
control design with ROS 4
Control systems
Coronaviruses
COVID-19
Decision making
Design
Integrated approach
Kinematics
Logistics
Mapping
Moving obstacles
navigation with ROS
navigation with ROS 3
Pandemics
Robotics
Robotics industry
Robots
ROS and LabVIEW interaction 1
Sensors
SLAM 5
Software
Velocity
Wheels
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Summary:The integration of intelligent robots in industrial production processes has the potential to significantly enhance efficiency and reduce human adversity. However, for such robots to effectively operate within human environments, it is critical that they possess an adequate understanding of their surroundings and are able to navigate through narrow aisles while avoiding both stationary and moving obstacles. In this research study, an omnidirectional automotive mobile robot has been designed for the purpose of performing industrial logistics tasks within heavy traffic and dynamic environments. A control system has been developed, which incorporates both high-level and low-level algorithms, and a graphical interface has been introduced for each control system. A highly efficient micro-controller, namely myRIO, has been utilized as the low-level computer to control the motors with an appropriate level of accuracy and robustness. Additionally, a Raspberry Pi 4, in conjunction with a remote PC, has been utilized for high-level decision making, such as mapping the experimental environment, path planning, and localization, through the utilization of multiple Lidar sensors, IMU, and odometry data generated by wheel encoders. In terms of software programming, LabVIEW has been employed for the low-level computer, and the Robot Operating System (ROS) has been utilized for the design of the higher-level software architecture. The proposed techniques discussed in this paper provide a solution for the development of medium- and large-category omnidirectional mobile robots with autonomous navigation and mapping capabilities.
ISSN:1424-8220
1424-8220
DOI:10.3390/s23063184