Optoelectronic Sensor Tracking for Mobile Robots
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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 digital image correlation, calculating relative position and orientation through cross-correlation processing.
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 uses optoelectronic sensors to capture images of the surface, creating optical copies of the environment. These image copies are then processed through cross-correlation algorithms to determine device position and orientation, replacing the need for complex SLAM systems while achieving comparable tracking accuracy
Solution Approach 2:
The patent replaces complex mechanical and computational SLAM systems with a simpler optical sensing and image processing approach. By substituting the mechanical/computational complexity of SLAM with optical field-based image correlation, the system achieves position tracking with reduced device complexity
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 system creates simplified optical copies (images) of the surface and processes these copies through efficient cross-correlation algorithms. This approach requires significantly less processing power compared to full SLAM computation while maintaining the ability to accurately track position and orientation changes
Solution Approach 2:
The patent changes the computational parameters from complex SLAM state estimation and map building to simpler image cross-correlation operations. This parameter change reduces the computational complexity and energy consumption while preserving the essential function of tracking device movement
3Device complexity
If simpler tracking methods are used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent substitutes a simple mechanical sensing approach (optoelectronic sensors capturing surface images) with a sophisticated image processing algorithm (cross-correlation). This substitution maintains measurement precision while keeping the hardware simple, as the complexity is shifted to software processing rather than hardware complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method allows for efficient tracking of a mobile robotic device's movement, reducing costs and processing requirements while ensuring thorough surface coverage without the need for expensive SLAM technology.
Implementation Method 1
two (or more) optoelectronic sensors are positioned on the underside of a mobile robotic device to monitor the surface below the device
Implementation Method 2
Successive images of the surface below the device are captured by the optoelectronic sensors and processed by an image processor using cross correlation to determine how much each successive image is offset from the last
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 The offset amount at one optoelectronic sensor may be compared to the offset amount at the other optoelectronic sensor to determine turning angle of the mobile robotic device.