AGV Reflector Matching via Triangle Perimeter
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Solution Overview
Problem
Conventional laser sensor positioning technologies face high computation burdens and inefficiencies, especially when calculating current position coordinates without prior base position information, and struggle with error control and accuracy in complex industrial scenes.
Innovation Solution
A reflector matching algorithm based on triangle perimeter matching, which records and combines coordinate information of reflectors, calculates triangle perimeters and side lengths, and uses these features to match detection triangles with basic triangles to determine the real-time position of an AGV with reduced computation burden and increased efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laser sensor positioning technology is used to calculate current position coordinates without prior base position information, then positioning can be performed globally, but the computation burden is extremely high and working efficiency is affected
Solution Approach 1:
The patent pre-calculates and stores all possible triangle perimeters formed by reflector combinations in the map area during the mapping phase. This preliminary action allows the positioning phase to only perform simple perimeter matching comparisons rather than complex coordinate calculations, thereby resolving the contradiction between positioning accuracy and working efficiency
Solution Approach 2:
The patent segments the positioning problem into two independent phases: map building phase (pre-computation of all triangle perimeters) and positioning phase (simple perimeter matching). This segmentation allows complex computations to be performed once during mapping, while real-time positioning only requires simple comparisons, thus improving working efficiency without sacrificing positioning accuracy
2Measurement precision
If polygon matching positioning is adopted, then positioning can be performed, but the computation burden is great and positioning accuracy is affected due to poor error control
Solution Approach 1:
The patent extracts the key identifying feature (triangle perimeter) from the complex polygon matching problem. By using only the perimeter length as the matching feature instead of full polygon geometry, the computation burden is greatly reduced while maintaining positioning accuracy, as the perimeter is invariant to the order of reflector detection
Solution Approach 2:
The patent changes the matching parameter from complex polygon geometry (multiple coordinates and angles) to a simple scalar value (perimeter length). This parameter change simplifies the matching process to a single-value comparison, reducing computation burden while the use of multiple reflector combinations maintains positioning accuracy through error control
Data Source
AI summary
A reflector matching algorithm based on triangle perimeter matching includes recording the position information of known reflectors in a map one by one, generating a scene coordinate point layout, taking points of the recorded reflectors and freely combining basic triangles with all side lengths not exceeding twice of the maximum detection distance of a laser sensor; recording all the combined basic triangles, then recording the corresponding side lengths, the position of each vertex, and the perimeter of each basic triangle, and saving the records in an AGV; reading the angle and distance information of the reflectors and freely combining detection triangles for the detected reflectors; and respectively calculating the side lengths and perimeters of the detection triangles, and searching and pairing in the basic triangle combination to determine the real-time position of the laser sensor.