Construction Inspection Trajectory Alignment for Accurate Plan Mapping
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Solution Overview
Problem
Existing construction inspection methods face challenges in accurately and efficiently associating inspection data sets with construction plans, requiring manual user input and time-consuming manual transformations of sensor-based trajectories to external coordinate systems, which are prone to errors.
Innovation Solution
A method and system that automatically aligns and scales inspection device trajectories with construction plans using geometric and time-related attributes, leveraging machine learning algorithms to correlate sensor data with construction models, thereby eliminating the need for manual localization and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual position logging by user is used to associate inspection data sets with construction plans, then flexibility and adaptability are maintained, but time consumption increases and accuracy decreases
Solution Approach 1:
The system performs automatic position logging where the inspection device itself records its trajectory and associates it with construction plan positions without requiring user input. The device uses its own sensors (GNSS, IMU, wheel encoders) to self-determine position and automatically transforms coordinates to match the construction plan coordinate system.
Solution Approach 2:
The manual mechanical process of user annotation is replaced with an automated electronic system using sensors, processors, and algorithms. The system substitutes human manual operations with automatic sensor-based trajectory recording and computational coordinate transformation.
2Productivity
If automatic position logging using sensors is used, then time efficiency improves, but device complexity increases
Solution Approach 1:
The inspection device is designed as a multi-functional platform that combines inspection imaging capabilities with navigation and positioning functions. The device integrates multiple sensors (GNSS receiver, IMU, wheel encoders) and processing units that serve both inspection data capture and automatic position logging functions simultaneously.
Solution Approach 2:
The system uses intermediate processing steps including coordinate transformation algorithms and trajectory smoothing filters that mediate between raw sensor data and final position associations. These intermediaries handle the complexity of multi-sensor fusion and coordinate system transformations automatically.
3Measurement precision
If manual coordinate transformation is used to transform trajectory to construction plan coordinate system, then accuracy can be controlled, but time consumption increases
Solution Approach 1:
The system performs preliminary coordinate transformation by establishing the transformation parameters (rotation angles, translation offsets, scale factors) between the inspection device's coordinate system and the construction plan's coordinate system before final position association. This preliminary setup enables automatic and accurate transformation of all trajectory points without time-consuming manual processing.
Data Source
AI summary
A method and system for construction inspection documentation with an inspection device moved at the construction along a trajectory, whilst capturing multiple inspection data sets. Thereby, there is automatically extracting first trajectory shape- and/or time-related attributes by evaluation of a shape and/or a timeline of the trajectory, automatically correlating extracted first attributes with corresponding second construction attributes provided by a stored construction plan or model, automatically aligning, and preferably also scaling, the trajectory using the construction plan or model as positional reference based on correlated first and second attributes. This enables automatically allocating a respective inspection data set to a position within the construction plan or model based on the aligned and scaled trajectory.