Pallet Front-Surface Detection Using 2D LiDAR Point Clouds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing pallet detection methods using 3D-LiDAR are costly and 3D cameras face accuracy issues due to sunlight interference and distance limitations, while 2D-LiDAR methods are time-consuming as they require vertical movement to acquire three-dimensional data.
Innovation Solution
A pallet detection device that uses a two-dimensional distance measurement device to acquire point cloud data, detects a straight line corresponding to the pallet's front surface without vertical movement, and calculates a score for point cloud points to select the most accurate line segment for position and orientation determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D-LiDAR is used to detect pallet position and orientation, then measurement precision is improved, but device cost increases significantly
Solution Approach 1:
The patent uses 2D-LiDAR to capture point cloud data and reconstructs three-dimensional information through computational methods instead of using expensive 3D-LiDAR hardware. The point cloud processing and straight line detection algorithms create a virtual 3D model from 2D measurements, achieving comparable detection accuracy at lower cost.
Solution Approach 2:
The patent replaces the mechanical/physical 3D-LiDAR measurement system with a computational approach using 2D-LiDAR point cloud data processing. Instead of physically measuring in three dimensions directly, the system uses algorithmic processing of 2D point clouds to extract pallet position and orientation information.
2Adaptability or versatility
If 3D camera is used to detect pallet position and orientation, then measurement capability is improved, but reliability deteriorates due to sunlight interference and distance limitations
Solution Approach 1:
The patent replaces optical 3D camera systems with a laser-based 2D-LiDAR system. Laser measurements are not affected by sunlight interference in the same way optical cameras are, and the point cloud processing methods enable reliable detection at various distances without the limitations of camera viewing angles and lighting conditions.
3Adaptability or versatility
If 2D-LiDAR is used with vertical movement to acquire three-dimensional data, then measurement capability is improved, but productivity decreases due to time-consuming measurement process
Solution Approach 1:
The patent processes two-dimensional point cloud data through computational methods to extract three-dimensional position and orientation information. Instead of physically moving the sensor to capture 3D data, the system uses mathematical processing of 2D point clouds to achieve 3D detection, eliminating the time required for vertical movement while maintaining measurement capability.
Solution Approach 2:
The patent replaces the mechanical vertical movement of the 2D-LiDAR with computational processing. The straight line detection algorithm processes point cloud data to extract pallet front surface information and calculate position and orientation without any physical movement, significantly reducing measurement time while maintaining detection accuracy.
4Productivity
If 2D-LiDAR is used without vertical movement to detect pallet, then productivity is improved by reducing measurement time, but measurement precision deteriorates due to inability to acquire three-dimensional data
Solution Approach 1:
The patent uses computational processing to extract three-dimensional position and orientation information from two-dimensional point cloud data. The straight line detection algorithm identifies the pallet front surface and calculates spatial parameters without requiring physical 3D scanning, achieving both speed and accuracy.
Solution Approach 2:
The patent changes the approach from physical 3D measurement parameters to 2D point cloud processing parameters. By using score-based evaluation and straight line detection algorithms on point cloud data, the system extracts accurate position and orientation information without requiring three-dimensional scanning, maintaining precision while improving productivity.
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 accurate and rapid detection of pallet position and orientation without moving the two-dimensional distance measurement device vertically, improving efficiency and reducing costs.
Implementation Method 1
a group of observation points on the same plane obtained by reflected light from the front surface of the pallet
Data Source
AI summary
Pallet detection device that acquires point cloud data indicating a point cloud measured by a two-dimensional distance measurement device on a depth map; detects a straight line corresponding to a front surface of a pallet based on the point cloud in a region presumed to include the front surface of the pallet in the point cloud data; detects a line segment indicating the front surface of the pallet based on the straight line; acquires position and orientation of the pallet based on the line segment. Acquires one or more straight line candidates and assigns for each of the one or more straight line candidates a score to the point cloud and selects the straight line from the one or more straight line candidates based on a score accumulated value obtained by accumulating the score for the point cloud in the region presumed to include the front surface of the pallet.