AMR Accuracy Measurement Using Optical Marker Offset Analysis
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Solution Overview
Problem
There is no effective method to measure the movement accuracy of autonomous mobile vehicles like AMR or AGV after purchase, relying solely on manufacturer-provided specifications, which can lead to inaccuracies and potential collisions.
Innovation Solution
An accuracy measurement method and device that calculates X-axis and Y-axis offsets using a light beam and image capture system, involving a distance calculating, regression center calculating, and average calculating steps to determine offsets, and a calculating device that is electrically coupled to the vehicle's processing system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manufacturer specifications are used to determine movement accuracy, then the process is simple and quick, but the measurement precision is insufficient and cannot verify true accuracy
Solution Approach 1:
The patent introduces a marker as an intermediary object between the autonomous mobile vehicle and the image capture device. The marker serves as a reference target that enables precise measurement of the vehicle's position and movement accuracy without requiring complex direct measurement systems. The marker's known pattern allows for accurate coordinate extraction and offset calculation.
Solution Approach 2:
The patent replaces mechanical measurement systems with an optical-based image capture and analysis system. Instead of using physical measurement tools or complex mechanical sensors, the system uses image capture devices to photograph the marker and processing devices to analyze the images, thereby determining movement accuracy through coordinate calculations and offset measurements.
2Measurement precision
If repeated measurements are performed multiple times to improve accuracy, then the measurement precision increases, but the measurement time increases
Solution Approach 1:
The patent employs periodic action by performing the measurement process multiple times (at least two times) and calculating average offsets from repeated measurements. This periodic repetition of the measurement cycle improves precision by averaging out errors while maintaining efficiency through systematic data collection and statistical processing.
Solution Approach 2:
The patent implements feedback by using the measured offsets to provide information about the autonomous mobile vehicle's positioning accuracy. The system calculates X-axis and Y-axis offsets from repeated measurements and uses this feedback information to assess whether the vehicle meets manufacturer specifications, enabling continuous improvement and verification of measurement results.
3Reliability
If a comprehensive measurement system is implemented to verify true accuracy, then the reliability of accuracy verification improves, but the device complexity increases
Solution Approach 1:
The patent segments the measurement system into distinct functional components: an image capture device for acquiring images, a processing device for analyzing images and calculating coordinates, and a marker as a reference target. This segmentation allows each component to perform its specific function efficiently, improving overall reliability while managing complexity through modular design.
Solution Approach 2:
The patent uses a marker with a known reference pattern that creates a reproducible image copy in the captured image. This known pattern serves as a reference frame that can be consistently identified and measured across multiple images, enabling reliable accuracy verification without requiring complex calibration procedures for each measurement.
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
Enables precise measurement of X-axis and Y-axis offsets, ensuring the vehicle's accuracy meets manufacturer tolerances, reducing collision risks and improving operational planning.
Implementation Method 1
a light beam emitting step is implemented to control a light beam device to emit at least one light beam toward a marker so as to form at least one light spot on the marker
Implementation Method 2
The image capturing step is implemented to control an image capture device to capture an image of the marker so as to form a to-be-analyzed image
Data Source
AI summary
An accuracy measurement method of an autonomous mobile vehicle, a calculating device, and an autonomous mobile vehicle are provided. The accuracy measurement method includes a distance calculating step, a regression center calculating step, and an average calculating step. The distance calculating step includes a controlling step, a light beam emitting step, an image capturing step, an image analyzing step, and a converting step. The regression center calculating step is performed after the distance calculating step is repeatedly performed by at least two times. The accuracy measurement method is performed to obtain an X-axis offset in an X-axis direction, a Y-axis offset in a Y-axis direction, and an angle deflection of an autonomous mobile vehicle.