3D Point Cloud Modeling with Encoder-Based Rotation Positioning
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Solution Overview
Problem
Current three-dimensional modeling using laser radars faces challenges in precision due to reliance on inertial measurement units and algorithmic estimation, leading to high costs and lower quality models.
Innovation Solution
A method and apparatus that utilize a point cloud collection device, electric motor, and encoder to obtain and determine precise rotation position information, allowing for accurate construction of three-dimensional panoramic models by converting point cloud data into X, Y, and Z-axis coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inertial measurement unit (IMU) and algorithmic estimation are used to determine splicing positions, then the system can function with mechanical rotary laser radars, but the cost increases and modeling precision deteriorates
Solution Approach 1:
The patent replaces the mechanical rotary laser radar system with an electric motor-driven point cloud collection device. This substitution eliminates the need for complex IMU systems and algorithmic estimation, directly achieving precise splicing positions through the encoder's direct measurement of motor rotation, thereby reducing system cost while maintaining or improving modeling precision.
Solution Approach 2:
The patent introduces an encoder as an intermediary component between the electric motor and the point cloud collection device. The encoder serves as a precise mediator that directly measures rotation position and provides accurate angular data for splicing, replacing the need for IMU and complex algorithms while reducing overall system complexity and cost.
2Productivity
If mechanical rotary laser radars are used with IMU for position determination, then data can be collected, but the data collection time increases and efficiency decreases
Solution Approach 1:
The patent replaces the mechanical rotary laser radar with an electric motor-driven system controlled by encoder feedback. This substitution enables more efficient data collection by allowing precise positioning and faster scanning speeds, directly improving productivity while reducing the time required for complete 360-degree scanning and processing.
3Manufacturing precision
If algorithmic estimation is used to determine splicing positions, then the system can operate without precise position sensors, but the modeling quality deteriorates
Solution Approach 1:
The patent introduces an encoder as a precise position sensor intermediary between the electric motor and the control system. This encoder directly measures rotation position with high accuracy, providing precise angular data for splicing operations and eliminating the need for complex algorithmic estimation, thereby improving splicing position accuracy while simplifying the overall system.
Solution Approach 2:
The patent replaces algorithmic estimation methods with a direct mechanical measurement approach using the encoder. This substitution provides accurate position data through physical measurement rather than computational estimation, significantly improving splicing precision while reducing algorithmic complexity.
Data Source
AI summary
A modeling method and apparatus based on point cloud data, an electronic device, and a storage medium are provided, and relate to the field of three-dimensional panoramic technologies. The modeling method based on point cloud data includes: obtaining three-dimensional point cloud information collected by a point cloud collection device from a scanned target, a first time information, first rotation position information of an electric motor, and a second time information; determining second rotation position information based on the first time information and the second time information; and obtaining position information of the scanned target based on the three-dimensional point cloud information and the second rotation position information, to construct a three-dimensional panoramic model corresponding to the scanned target.