Laser Scanning Plan Optimization for Extended Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current terrestrial laser scanning methods require multiple setups and are time-consuming when surveying extended objects, as they often necessitate combining multiple scans to achieve complete coverage, especially for objects with obstructed or angled surfaces, and mobile scanners lack the accuracy for large areas.
Innovation Solution
A method for automatically generating an optimal scanning plan that calculates the best positions for stationary and mobile laser scanners to minimize setups, walking distance, and ensure complete coverage, considering optimization criteria such as point density and overlap, and allows for real-time updates based on scan data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple laser scans are performed to achieve complete coverage of extended objects, then measurement completeness is improved, but scanning time and productivity deteriorate
Solution Approach 1:
The system performs preliminary actions by calculating an optimal scanning plan before actual scanning begins. The planning module determines the minimum number of required standpoints and their optimal positions in advance, preventing unnecessary scans and setups. This preliminary planning ensures complete coverage while minimizing scanning time and productivity loss.
2Reliability
If the number of scanner setups is increased to cover all object surfaces, then measurement completeness is improved, but time consumption and productivity deteriorate
Solution Approach 1:
The system calculates the optimal number and positions of scanner standpoints in advance before actual scanning begins. By performing this preliminary planning, the system determines the minimum setups required to achieve complete coverage, thereby reducing unnecessary setup time while ensuring all object surfaces are captured.
Solution Approach 2:
The scanning plan is dynamically adapted based on object geometry and measurement requirements. The system adjusts the number and positioning of standpoints according to the specific characteristics of each object, optimizing the balance between coverage completeness and setup time for different scanning scenarios.
3Measurement precision
If high scanning resolution is used for all areas, then measurement precision is improved, but data volume and processing time deteriorate
Solution Approach 1:
The system applies different scanning resolutions to different areas of the object based on their importance and geometric characteristics. Critical areas with complex geometry or high measurement requirements receive higher point density, while less important areas use lower resolution. This local quality approach maintains measurement precision where needed while significantly reducing overall data volume and processing time.
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 method reduces the time and effort required for scanning by determining the most efficient arrangement of scanning points and devices, ensuring comprehensive coverage with minimal unnecessary data collection and improving accuracy by strategically using both high-accuracy stationary and low-accuracy mobile scanners.
Implementation Method 1
the laser scanner using a laser beam which is moved over the object in a predefined manner
Implementation Method 2
The point cloud is derived by determining a distance for each measuring point and a correlated direction of the laser beam
Data Source
AI summary
A method for automatically establishing an optimal laser scanning plan, the scanning plan indicating an optimal arrangement of multiple distributed standpoints, the arrangement enabling a scanning of an extended object by multiple terrestrial scans of different parts of the object at respective standpoints.