Picture Compilation System for Autonomous Mining Zone Integration
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Solution Overview
Problem
Current automation systems in complex industrial environments, such as mining, face challenges in efficiently managing autonomous operations across diverse and dynamic geographical regions with heterogeneous data, leading to limitations in equipment coordination and resource extraction optimization.
Innovation Solution
A method and apparatus for generating a data representation of a geographical region by receiving information on localized zones, associating and fusing heterogeneous data into common data representations, and integrating them to support autonomous operations, utilizing a system that includes pre-extraction, equipment, and post-extraction modeling units to create a comprehensive model of the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous operations are implemented in complex industrial environments, then operational efficiency and safety are improved, but system complexity and difficulty of managing heterogeneous data increase
Solution Approach 1:
The system divides the geographical region into multiple localised zones with operation-defined geographical boundaries. Each zone can be independently managed and monitored, allowing autonomous operations to be broken down into manageable segments rather than controlling the entire complex environment as a single system.
Solution Approach 2:
A picture compilation system acts as an intermediary layer between heterogeneous data sources and autonomous operation controllers. This system receives data from multiple sources, compiles it into a unified representation, and provides it to control systems, thereby managing complexity without sacrificing operational efficiency.
2Loss of information
If heterogeneous data from multiple sources is integrated, then comprehensive environmental modeling is improved, but data processing complexity and time requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-defining localised zones and their geographical boundaries before data collection begins. Data sources are pre-configured to provide information specific to these zones, allowing for more efficient processing since the framework for integration is established in advance rather than requiring post-hoc organization of heterogeneous data.
Solution Approach 2:
The picture compilation system serves multiple functions simultaneously: it receives heterogeneous data from various sources, associates data with specific localised zones, fuses data within each zone, and integrates zone representations into a common geographical region model. This multi-functionality reduces the need for separate processing steps and minimizes overall processing time.
3Measurement precision
If multiple localised zones are defined within a geographical region, then equipment coordination precision is improved, but system configuration complexity increases
Solution Approach 1:
The geographical region is segmented into multiple localised zones with clearly defined operation-defined geographical boundaries. This segmentation enables precise equipment coordination within each zone while providing a hierarchical structure that simplifies overall system configuration compared to managing the entire region as a single complex unit.
Solution Approach 2:
The system introduces a spatial dimension by organizing zones geographically within the larger region. This dimensional approach allows equipment coordination precision to be improved through location-specific zone definitions while configuration complexity is managed through the natural hierarchical relationship between zones and the overall geographical region.
Data Source
AI summary
Methods and systems are described for generating a data representation of a geographical region as an adjunct to conducting autonomous operations within the region. The method comprises receiving information specifying a plurality of localized caused zones having operation-defined geographical boundaries within the region; receiving heterogeneous data descriptive of the region; associating the received data with respective localized zones; fusing the received data associated with the localized zones into data representations of the localized zones; and integrating the data representations of the localized zones into a common data representation of the geographical region.