Optical Tracking Module Using Sine-Cosine Displacement Computation
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Solution Overview
Problem
Conventional optical navigation systems face challenges in effectively tracking mobile robotic devices across various environments and surfaces due to limitations such as wheel slippage and performance issues at low speeds, especially when compared to encoder-based systems.
Innovation Solution
A system and method for optically tracking a mobile device using a light source, image sensor array, navigation engine, and tracking module that computes displacement values along different directions to determine the current position, utilizing sine and cosine functions based on previous displacement values to improve tracking accuracy across diverse surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If encoder-based systems are used to track movements of mobile robotic devices, then tracking is reliable on wheel slippage and at low speeds, but the system cannot effectively track across various environments and surfaces
Solution Approach 1:
The patent replaces encoder-based mechanical tracking with an optical navigation system that uses image sensors to capture and analyze visual patterns on the navigation surface. This substitution enables the system to track movement through optical correlation of successive frames rather than through mechanical wheel encoders, providing adaptability across different surfaces while maintaining tracking reliability through sophisticated image processing algorithms that compensate for wheel slippage and low-speed conditions.
2Adaptability or versatility
If conventional optical navigation systems are used, then tracking is achieved through image correlation, but the systems do not work well in different environments or surfaces
Solution Approach 1:
The patent implements dynamic adaptation by continuously adjusting tracking parameters based on real-time analysis of the navigation surface characteristics. The system dynamically modifies correlation algorithms, exposure times, and illumination patterns according to the detected surface properties, enabling precise tracking across diverse environments while maintaining adaptability to changing conditions through feedback-driven parameter optimization.
3Reliability
If optical navigation systems are used instead of encoders, then performance issues at low speeds and wheel slippage are avoided, but the systems face limitations in different environments
Solution Approach 1:
The patent creates a universal optical tracking system that can operate effectively across multiple surface types and environmental conditions by integrating multiple sensing modalities and adaptive algorithms. The system uses image sensors, illumination sources, and correlation processing that can adapt to various navigation surfaces, making it universally applicable while maintaining the reliability advantages of optical tracking over encoder-based systems.
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
The solution enables accurate and reliable optical tracking of mobile devices on different surfaces and environments, reducing errors associated with wheel slippage and low-speed performance issues, while maintaining robustness and precision.
Implementation Method 1
The light source is configured to emit illumination light toward a navigation surface. The image sensor array is positioned to receive the illumination light reflected from the navigation surface.
Data Source
AI summary
A system and method for optically tracking a mobile device uses a first displacement value along a first direction and a second displacement value along a second direction, which are produced using frames of image data of a navigation surface, to compute first and second tracking values that indicate the current position of the mobile device. The first tracking value is computed using the second displacement value and the sine of a tracking angle value, while the second tracking value is computed using the second displacement value and the cosine of the tracking angle value. The tracking angle value is an angle value derived using at least one previous second displacement value.