Central 3D Map Feedback for Precise Construction Site Positioning
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Solution Overview
Problem
Construction sites present challenging environments for precise positioning due to obstructions, rapid changes, and the limitations of existing positioning technologies like GNSS, total stations, and inside-out tracking systems, which are costly, require training, and may not meet precision needs.
Innovation Solution
A central map is created and updated using a feedback loop from various sensors, including laser scanners, AR devices, and robots, aggregating data to provide a dynamic, real-time 3D map that can be used for precise positioning and orientation of devices, enhancing existing systems with redundancy and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional positioning technologies (GNSS, total stations, inside-out tracking) are used, then positioning can be achieved, but the cost is high, training is required, and precision needs may not be met due to obstructions and rapid changes
Solution Approach 1:
The system segments the positioning task by dividing the construction site into multiple zones, each with its own local map and positioning references. Multiple independent positioning systems operate in parallel across different zones, with each handling localized positioning independently. This segmentation allows the system to achieve high precision in each zone without requiring a single complex system to cover the entire site.
Solution Approach 2:
The system creates a universal map data structure that serves multiple functions: it provides positioning references for multiple devices simultaneously, acts as a feedback mechanism for map updates, and supports both initial orientation and continuous positioning. The same map infrastructure is used by AR devices, robots, and surveying equipment, eliminating the need for separate positioning systems for each device type.
2Reliability
If a central map system with feedback loop is implemented, then precise positioning and real-time updates are achieved, but data aggregation and processing complexity increases
Solution Approach 1:
The system implements a feedback loop where devices use the central map for positioning, then feed back their observed data to update the map. AR devices capture images that are compared against the map, robots provide odometry and sensor data, and surveying equipment contributes precise measurements. This continuous feedback improves map accuracy and reliability over time, making the system more robust while the processing is distributed across multiple devices rather than centralized in one complex processor.
Solution Approach 2:
The central map acts as an intermediary data structure that mediates between multiple positioning devices and the physical environment. Rather than devices directly communicating with each other or with a complex central processor, they all interact through the standardized map interface. This intermediary simplifies data integration by providing a common framework for receiving, storing, and distributing positioning information.
3Loss of information
If multiple devices aggregate data to update the map, then map accuracy and completeness improve, but communication and coordination overhead increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing key features in the map before they are needed for positioning. The map is continuously updated in the background with data from various sources, so when a device needs positioning information, the relevant data is already prepared and available. This eliminates the need for time-consuming data aggregation at the moment of positioning requests.
Solution Approach 2:
The map update process operates continuously in the background rather than in discrete batches. Devices continuously stream their sensor data and observations to the map system, which continuously integrates and updates the map state. This continuous operation ensures the map remains current without requiring periodic stop-and-go data aggregation cycles, reducing time loss while maintaining complete and accurate information.
Data Source
AI summary
A central map can be used in a construction environment to help position devices and receive updates from devices to update the central map. Devices in the construction environment, such augmented-reality devices, laser scanners, total stations, satellite navigation receivers, and others can be used to provide “crowd-sourced” data to update the central map as the construction environment changes.