Grid Survey Module Using IMU Mapping for Rail Level Deviation
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Solution Overview
Problem
Automated storage and retrieval systems face issues due to level deviations and height differences in the grid cells, leading to wear and tear, damage to containers and handling vehicles, and potential system halts from uneven surfaces.
Innovation Solution
Implement a method using orientation sensors, such as IMUs, on container handling vehicles to measure pitch and roll, calculate height differences, and generate maps to identify and adjust level deviations in the grid cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sampling methods are used, then the sampling process is simple, but the representativeness and accuracy of the collected data are insufficient
Solution Approach 1:
The sampling area is divided into multiple grid sections with different sampling probabilities. High-variance areas are segmented into more sections with higher sampling rates, while low-variance areas use fewer sections with lower sampling rates, optimizing both accuracy and efficiency
Solution Approach 2:
The sampling probability and number of samples are dynamically adjusted based on the calculated variance of each grid section. Sections with higher variance receive higher sampling probabilities, allowing the system to adapt to different data distributions and improve representativeness
2Measurement precision
If comprehensive data collection is performed, then the data representativeness is improved, but the time and resources required increase significantly
Solution Approach 1:
The sampling probability parameter is changed dynamically based on the variance of each grid section. By adjusting this parameter, the system collects more data from high-variance areas and fewer data points from low-variance areas, improving accuracy while reducing overall sampling time and resource consumption
3Productivity
If uniform sampling is applied across all areas, then the sampling process is straightforward, but the efficiency and resource utilization are suboptimal
Solution Approach 1:
Different sampling probabilities are assigned to different grid sections based on their local characteristics (variance). High-variance sections receive higher sampling probabilities while low-variance sections receive lower probabilities, optimizing resource allocation and sampling efficiency for each local area
Data Source
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AI summary
A method of measuring level deviation in an automated storage and retrieval system, wherein the system comprises: a rail system comprising a first set of parallel rails arranged to guide movement of a container handling vehicle in a first direction (X) across the top of a frame structure, and a second set of parallel rails arranged perpendicular to the first set of rails to guide movement of the container handling vehicle in a second direction (Y) which is perpendicular to the first direction (X), the first and second sets of parallel rails dividing the rail system into a plurality of grid cells, at least one container handling vehicle configured to operate on the rail system, wherein the at least one container handling vehicle is provided with at least one orientation sensor configured to measure at least one orientation parameter of the sensor in a three-dimensional cartesian reference system, a central control unit configured to receive, transmit and process data signals of the container handling vehicle and to receive and process data signals of the sensor, wherein the method comprises the steps of: arranging the container handling vehicle in a predetermined position on the grid, transmitting a data signal from the central control unit to the container handling vehicle commanding the container handling vehicle to move a distance in one direction (X, Y) along the grid, measuring at predetermined intervals, using the orientation sensor, at least one orientation parameter to produce orientation measurements that are indicative of the container handling vehicle's orientation within the three-dimensional cartesian reference system, transmitting data concerning the orientation measurements to the central control unit, and processing the orientation measurements using the central control unit in order to identify portions of the rail system that deviate from predetermined values.