Optical Flow Odometry Using Sensor Cluster for Error Correction
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Solution Overview
Problem
Odometric technology based on optical mouse sensors is sensitive to errors due to defective digital image captures, which can lead to miscomputation of position and trajectory, particularly in GPS-denied environments, and requires additional odometric systems for correction.
Innovation Solution
The use of a cluster of optical mouse sensors instead of a single sensor, where the sensors are arranged in a specific geometrical configuration, allows for the detection and correction of errors due to defective image captures, eliminating the need for auxiliary odometric systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single optical mouse sensor is used for odometry, then the device complexity and cost are reduced, but the reliability and measurement precision deteriorate due to defective digital image captures
Solution Approach 1:
The patent divides the single sensor system into a cluster of multiple optical mouse sensors arranged in a specific geometrical configuration. Each sensor independently captures digital images, and the system processes these segmented measurements to compute position and trajectory, thereby reducing the impact of any single defective capture.
Solution Approach 2:
The patent implements beforehand cushioning by using multiple sensors to capture images simultaneously, creating redundancy before errors occur. When defective digital image captures are detected, the system can compensate using data from the other functional sensors, cushioning against the impact of failures.
2Ease of manufacture
If a single optical mouse sensor is used for odometry, then the manufacturing cost is reduced, but the measurement precision deteriorates due to error accumulation
Solution Approach 1:
The patent segments the measurement function across multiple optical mouse sensors, each capturing images independently. This segmentation allows the system to aggregate precise measurements from multiple sources, improving overall measurement precision while maintaining the cost-effectiveness of using standard optical mouse sensor technology.
Solution Approach 2:
The patent uses multiple copies of the same optical mouse sensor technology arranged in a geometrical configuration. These copies capture images simultaneously and provide redundant measurements that can be processed to achieve higher precision without requiring expensive specialized sensors.
3Reliability
If additional odometric systems are added to correct errors, then the reliability and measurement precision improve, but the device complexity and cost increase
Solution Approach 1:
The patent makes the cluster of optical mouse sensors multi-functional by using them both for primary odometry measurements and for error detection and correction. The same sensors that capture images for position computation also provide redundant data for detecting and correcting defective captures, eliminating the need for separate auxiliary odometric systems.
Solution Approach 2:
The patent implements self-service by enabling the optical mouse sensor cluster to correct its own errors using its own redundant measurements. The system detects defective digital image captures and corrects position computation errors using data from the same sensor cluster, without requiring external correction 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
This approach significantly reduces the likelihood of error accumulation, enabling accurate and reliable position computation and trajectory determination without the need for additional odometric systems, thereby enhancing the cost-effectiveness and simplicity of the optical flow odometer.
Implementation Method 1
a light detector, such as a photodiode array or, more commonly, a CMOS (Complementary Metal-Oxide-Semiconductor) sensor, also known as APS (Active Pixel Sensor)
Data Source
AI summary
An optical flow odometer to determine the position of an object movable relatively to a surface is provided that includes a cluster of digital image sensors intended to be arranged on the movable object at respective reference positions and an electronic processing and control unit electrically connected with the digital image sensors and configured to: operate the digital image sensors in subsequent time instants during movement of the movable object so as to carry out a sequence of multiple digital image capture operations, in each of which the digital image sensors are operated to simultaneously capture respective digital images, and receive from the digital image sensors and process the digital images captured in the multiple digital image capture operations to compute either the positions of the individual digital image sensors or the position of the cluster of digital image sensors at one or more of the multiple digital image capture operations, and compute the position of the movable object at one or more multiple digital image capture operations based on either the positions of one or more individual digital image sensors or the position of the cluster of digital image sensors computed at one or more multiple digital image capture operations.