Surveying System with Real-Time Point Cloud Gap Detection
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Solution Overview
Problem
Existing surveying systems face challenges in efficiently acquiring three-dimensional point cloud data, particularly in identifying and addressing areas with insufficient data, which requires repeated measurements and complex navigation in virtual spaces.
Innovation Solution
The proposed surveying system utilizes a scanner device that can automatically acquire missing data points while mounted on a moving object, reducing the number of measurements and movements needed, and allows for real-time data display and monitoring on a terminal device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If measurement is repeated until three-dimensional point cloud data satisfies a necessary amount, then data completeness is improved, but measurement time and operational complexity increase
Solution Approach 1:
The system calculates point cloud amount for each unit segment and provides feedback by displaying insufficient areas on a map. This allows operators to see exactly where additional measurements are needed, enabling targeted re-measurement rather than random or repeated full-area scanning, thus reducing total measurement time while ensuring data completeness.
Solution Approach 2:
The surveying area is divided into multiple unit segments, and point cloud amount is calculated for each segment independently. This segmentation allows the system to identify specific segments with insufficient data and direct operators to only those areas, rather than requiring repeated measurements of the entire area, thereby reducing overall measurement time.
2Loss of information
If only virtual space checking is used to identify insufficient point cloud data, then data analysis capability is improved, but ease of field operation deteriorates
Solution Approach 1:
A map display serves as an intermediary between the virtual point cloud data and the physical field environment. The map visually represents unit segments with insufficient point cloud data, bridging the gap between abstract data analysis and concrete field navigation, making it easy for operators to locate and navigate to specific areas requiring additional measurements.
3Measurement precision
If manual navigation to insufficient data areas is required, then measurement precision is maintained, but operational burden increases
Solution Approach 1:
The system automatically calculates point cloud amounts, identifies insufficient unit segments, and generates visual guidance on a map display. This self-service capability reduces the operational burden by eliminating manual data analysis and navigation planning, while the system maintains measurement precision by providing accurate, data-driven guidance to specific locations requiring additional measurements.
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
This approach enables more efficient data acquisition, reduces the operational burden on operators, and allows for real-time monitoring and updating of three-dimensional point cloud data, ensuring that data is always up-to-date and sufficient.
Implementation Method 1
the scanner device or scanner unit may rotationally irradiate laser pulsed light through a scanning unit, scans a measuring object, and performs a distance measurement and an angle measurement by each pulsed light so as to acquire three-dimensional point cloud data
Data Source
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AI summary
A surveying system (1) includes an information processing device (100) and a surveying device (420) and further includes a scanner unit (260) configured to perform a measurement to acquire three-dimensional point cloud data on the surveying device (420), a measurement position specifying unit (127) configured to specify a measurement position for which three-dimensional point cloud data needs to be acquired, a position acquisition unit (270) configured to acquire a self-position of the surveying device (420), and a measurement computing unit (223) configured to perform a computation to measure the measurement position from the self-position.