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Leader-Follower Approach for Non-Holonomic Mobile Robots Based on Extended Kalman Filter Sensor Data Fusion and
Arpit Joon1, Wojciech Kowalczyk1
1Institute of Automatic Control and Robotics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznan, Poland.
Sensors (Basel, Switzerland)
|November 14, 2023
Summary
This study introduces a leader-follower mobile robot control system using onboard sensors and ArUco markers for precise localization. The enhanced perception range and data fusion improve robot pose estimation for effective navigation.
Area of Science:
- Robotics
- Computer Vision
- Control Systems
Background:
- Leader-follower robot systems require robust localization for coordinated tasks.
- Onboard sensors and visual markers are crucial for relative robot positioning.
- Expanding sensor perception range enhances localization accuracy in dynamic environments.
Purpose of the Study:
- To develop and validate a leader-follower mobile robot control approach.
- To enhance robot localization using a rotating camera platform and ArUco markers.
- To integrate sensor data for improved pose estimation.
Main Methods:
- Utilized an Intel RealSense camera on a rotating platform for expanded perception.
- Implemented ArUco markers and fiducial landmarks for robot-to-robot and workspace localization.
- Employed behavior trees for camera rotation control and Extended Kalman Filter (EKF) for sensor data fusion (encoders, IMUs).
- Integrated the Robot Operating System (ROS) for system implementation.
Main Results:
- Demonstrated effective robot-to-robot and workspace localization using onboard sensors and ArUco markers.
- The rotating platform successfully expanded the follower robot's perception range.
- EKF-based data fusion improved the accuracy of robot pose determination.
- Experimental validation confirmed the effectiveness of the proposed control algorithm.
Conclusions:
- The leader-follower control approach with enhanced perception and data fusion is effective for mobile robot navigation.
- The integration of a rotating camera, ArUco markers, and EKF provides robust localization capabilities.
- This method offers a reliable solution for coordinated multi-robot operations.
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