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A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots
Cosimo Patruno1, Roberto Colella1, Massimiliano Nitti1
1Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, Italian National Research Council, STIIMA-CNR, G. Amendola 122 D/O, Bari 70126, Italy.
Sensors (Basel, Switzerland)
|February 12, 2020
Summary
This study introduces a vision-based visual odometer for indoor robot localization. The method accurately estimates the pose of automatic guided vehicles (AGVs) in industrial settings with minimal error.
Area of Science:
- Robotics
- Computer Vision
- Indoor Navigation
Background:
- Accurate indoor robot localization is crucial for industrial automation.
- Existing methods often struggle with precision in dynamic environments.
Purpose of the Study:
- To develop a robust vision-based visual odometer for precise indoor robot localization.
- To estimate the relative pose of omnidirectional automatic guided vehicles (AGVs).
Main Methods:
- Utilizing a monocular downward-looking camera to capture floor images.
- Employing keypoint detection and feature matching with robust filtering for accurate correspondences.
- Implementing camera pose compensation to enhance positioning accuracy.
Main Results:
- Achieved a final positioning percentage error of 0.21% over 17.2 m in laboratory settings.
- Demonstrated 0.94% error over 80 m in an industrial environment.
- Reported an average relative positioning error of approximately 3%, aligning with state-of-the-art.
Conclusions:
- The proposed vision-based visual odometer offers high accuracy for indoor AGV localization.
- The method is effective in both controlled laboratory and real-world industrial environments.
- This approach contributes to improved navigation and automation in industrial settings.
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