Foundation Column Grid Positioning With Survey Feedback Control
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Solution Overview
Problem
The construction industry faces challenges in achieving precise and cost-effective installation of foundation column grids on sites with topography or access obstacles, leading to increased costs without improved quality or durability.
Innovation Solution
A robotics-assisted foundation installation system that uses live-streamed data from a total surveying station to a grid control system to precisely position column tops, allowing for global optimization of the column array and enabling precise alignment of prefabricated structures on difficult build sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional construction methods are used on difficult build sites, then construction costs increase, but precision and quality of column placement do not improve
Solution Approach 1:
The system performs preliminary positioning calculations and predictions before actual column installation. The machine learning model predicts optimal column positions based on site conditions, allowing workers to prepare accordingly and avoid costly repositioning during construction.
Solution Approach 2:
The system continuously monitors column placement in real-time and provides feedback to adjust positioning. Sensors track actual column positions and compare them against predicted positions, enabling dynamic corrections to maintain precision without increasing overall construction costs.
2Adaptability or versatility
If taller foundation columns are used to accommodate topography variations, then adaptability to difficult sites improves, but the risk of failing to achieve required top of column machine tolerance increases
Solution Approach 1:
The system dynamically adjusts column positioning strategies based on real-time measurements and predictions. As columns of varying heights are installed to accommodate topography, the system continuously updates position predictions and adjusts subsequent column placements to maintain required tolerances at column tops.
Solution Approach 2:
The machine learning model changes key parameters such as predicted column positions, required adjustments, and tolerance thresholds based on input data including column height, site topography, and previous placement accuracy. This allows the system to optimize each column placement individually while maintaining overall precision.
3Adaptability or versatility
If more variety in offset heights is used to match rolling topography, then adaptability to challenging sites improves, but alignment precision and spatial overlap prevention become more difficult
Solution Approach 1:
The system performs preliminary spatial analysis and collision detection before column installation. The machine learning model predicts potential spatial overlaps and alignment issues based on planned column positions and heights, allowing workers to adjust the plan beforehand to prevent costly rework.
Solution Approach 2:
The system provides real-time feedback on spatial relationships between columns with varying offset heights. As each column is positioned, the system monitors its relationship to previously installed columns and predicts potential conflicts, enabling proactive adjustments to maintain precise spatial alignment.
Data Source
AI summary
A robotics-assisted foundation installation system is provided in which data reporting the X, Y, and Z positions of foundation column tops are sent from a total surveying station to a grid control system. The grid control system receives the data and associates specific data with specific columns in an array—the “grid.” The grid control system compares the actual positions of the columns in the grid to target positions that were determined based on the requirements of the structure to be supported. After determining differences between the actual positions and the target positions, the grid control system sends instructions to column positioning tools associated with the individual columns. Actuators in a column positioning tool are directed by the grid control system to adjust the position of the associated column. Once the live streamed data confirms that each column is in the proper position, the columns are fixed in place.