Handheld Printer Optical Positioning via Dimensionality Reduction
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Solution Overview
Problem
Handheld printers face challenges in maintaining print quality due to limitations in sensor capabilities, leading to lost or inaccurate printer location calculations, resulting in incomplete or poor print jobs, especially in areas without typographic structures and requiring high computational complexity for optical sensor correlations.
Innovation Solution
The implementation of an optical navigation system that reduces the size of position sensor signals to one-dimensional or two-dimensional matrices for efficient correlation, using enhanced search algorithms and distortion functions to minimize computation, and incorporating an intake checker for signal validity assessment, facilitating real-time processing and improved print quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical sensors are used to track printer position in random motion patterns, then positioning capability is improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the high-dimensional sensor data into smaller, manageable components by dividing the sensor array into multiple zones and processing each zone separately. This segmentation reduces the computational burden while maintaining positioning accuracy, as the system can process multiple smaller data sets in parallel rather than one large data set sequentially.
Solution Approach 2:
The patent transforms the positioning problem from a complex multi-dimensional correlation task into a simpler one-dimensional search problem by projecting sensor data onto a linear scale. This dimensionality reduction allows the system to find position matches much more quickly, reducing computational complexity while preserving the essential positioning information.
2Measurement precision
If full-resolution sensor data is processed for position correlation, then positioning accuracy is improved, but processing speed decreases
Solution Approach 1:
The patent extracts only the essential features from full-resolution sensor data that are necessary for positioning, discarding redundant information. By taking out only the critical position-correlating elements from the complete sensor data set, the system maintains positioning accuracy while dramatically reducing the amount of data that needs to be processed, thereby increasing processing speed.
3Measurement precision
If typographic structure identification is used for positioning, then position determination is improved, but coverage area is limited
Solution Approach 1:
The patent creates a universal positioning system that can identify and process multiple types of media features, not just typographic structures. The system is designed to work with various patterns and features on the media surface, making it multi-functional and applicable to a broader range of media types and printing scenarios, thereby expanding coverage area while maintaining positioning capability.
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 solution enables robust, multi-directional, and random printing with improved print quality by accurately determining printer position and reducing computational complexity, ensuring reliable and efficient handheld printing operations.
Implementation Method 1
a position sensor transmits and receives light from the media
Data Source
AI summary
Methods and apparatus include a handheld printer manipulated by an operator to print an image on a media. A controller correlates a location of a printhead to the image and causes printing or not. A position sensor provides input to the controller. Its signal typifies pixels in a matrix frame indicating a current position frame and, over time, a previous position frame. The controller compares the two frames to find a presence of the previous in the current. To improve computational efficiency, the controller reduces a relative size of both frames before comparing. Specific reduction techniques contemplate converting a matrix frame of pixels indicative of previous and current locations into smaller matrices, including one-dimensional forms. Possible search areas within the current frame to look for the previous frame utilize knowledge about the movement history of the printer. Position sensor signal validity and controller architectures are other noteworthy features.