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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
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Design and Implementation of an Integrated Control System for Omnidirectional Mobile Robots in Industrial Logistics
Ahmed Neaz1, Sunyeop Lee1, Kanghyun Nam1
1School of Mechanical Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan 38541, Republic of Korea.
Sensors (Basel, Switzerland)
|March 30, 2023
Summary
This study introduces an omnidirectional mobile robot for industrial logistics, enhancing safety and efficiency in dynamic environments. It features advanced navigation and mapping for autonomous operation, crucial for intelligent manufacturing.
Area of Science:
- Robotics
- Industrial Automation
- Artificial Intelligence
Background:
- Intelligent robots are increasingly integrated into industrial production to boost efficiency and safety.
- Effective operation in human environments requires robots to understand surroundings and navigate complex spaces.
- Autonomous navigation and obstacle avoidance are critical for robots in dynamic industrial settings.
Purpose of the Study:
- To design an omnidirectional automotive mobile robot for industrial logistics in busy, dynamic environments.
- To develop a robust control system with high-level and low-level algorithms for autonomous navigation.
- To enable autonomous mapping, path planning, and localization for medium- and large-category robots.
Main Methods:
- Designed an omnidirectional mobile robot utilizing a myRIO micro-controller for low-level motor control.
- Employed Raspberry Pi 4 and a remote PC for high-level decision-making, including mapping and path planning.
- Integrated multiple Lidar sensors, Inertial Measurement Unit (IMU), and wheel encoder odometry data.
- Utilized LabVIEW for low-level programming and Robot Operating System (ROS) for high-level software architecture.
Main Results:
- Successfully developed a control system with integrated high-level and low-level algorithms.
- Demonstrated the capability for accurate motor control and robust navigation in simulated industrial environments.
- Achieved autonomous mapping, localization, and path planning using sensor fusion and ROS.
Conclusions:
- The developed system provides a viable solution for creating autonomous omnidirectional mobile robots for industrial logistics.
- The integration of myRIO, Raspberry Pi 4, and ROS enables efficient and robust autonomous navigation.
- The proposed techniques are scalable for medium- and large-category robots, enhancing industrial automation capabilities.
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