Mobile Robot Surface Tracking Using Dual Optical Sensors
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Solution Overview
Problem
Existing methods for tracking the movement of mobile robotic devices, such as SLAM, are costly and require significant processing power, necessitating a simpler and more efficient approach to ensure thorough surface coverage.
Innovation Solution
Positioning two optoelectronic sensors on the underside of a mobile robotic device to capture and process images using cross-correlation, determining relative position and orientation through digital image correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM technology is used to determine position and orientation, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex SLAM technology with a simpler optoelectronic sensing system that uses image capture and cross-correlation algorithms to track surface patterns. This substitutes sophisticated localization algorithms with a more straightforward optical measurement approach, reducing device complexity while maintaining measurement precision for position and orientation tracking.
Solution Approach 2:
The system captures optical images of the surface as copies of the physical environment. By working with these image copies rather than direct complex sensor fusion, the system simplifies the measurement process. The cross-correlation of successive images provides position and orientation information without requiring full SLAM infrastructure.
2Measurement precision
If SLAM technology is used to determine position and orientation, then measurement precision is improved, but processing power requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for position and orientation tracking by capturing images and computing cross-correlation offsets. This extracts the minimum necessary data from the environment, avoiding the intensive processing of full SLAM systems while maintaining sufficient precision for navigation and coverage tracking.
Solution Approach 2:
The system performs partial localization by tracking only the relative displacement between successive image frames through cross-correlation, rather than performing complete simultaneous localization and mapping. This partial action approach reduces processing power consumption while providing adequate position and orientation information for the robotic device's navigation needs.
3Device complexity
If simpler tracking methods are used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system utilizes optical contrast and pattern variations in the environment captured by the optoelectronic sensors. By detecting changes in the visual appearance of the surface across successive images, the cross-correlation algorithm can precisely measure displacement and orientation changes, maintaining measurement precision despite the simplicity of the overall system.
Data Source
AI summary
A method for tracking movement and turning angle of a mobile robotic device using two optoelectronic sensors positioned on the underside thereof. Digital image correlation is used to analyze images captured by the optoelectronic sensors and determine the amount of offset, and thereby amount of movement of the device. Trigonometric analysis of a triangle formed by lines between the positions of the optoelectronic sensors at different intervals may be used to determine turning angle of the mobile robotic device.