Reduced Evidence Grid Correlation for Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The large amount of data in evidence grids, particularly historical and current grids, consumes significant memory and processing time, hindering timely correlation and navigation applications with faster time requirements.
Innovation Solution
The evidence grids are reduced in size by removing data representing empty space or data not associated with edges or features, and different searching methods such as global, sequential, and segmented searches are implemented to efficiently cross-correlate them, producing navigation parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If evidence grids contain complete data describing empty space and space inside objects, then navigation accuracy is improved, but memory consumption increases significantly
Solution Approach 1:
The patent extracts and removes unnecessary data from evidence grids, specifically eliminating redundant information about empty space and interior spaces of objects. Only essential boundary and feature data are retained, directly reducing memory consumption while preserving navigation-relevant information
Solution Approach 2:
The patent creates a simplified representation (copy) of the environment that captures only the essential navigational features rather than complete spatial data. This reduced evidence grid serves as a functional copy sufficient for navigation tasks without the full detail of the original complete spatial model
2Measurement precision
If evidence grids contain complete data describing empty space and space inside objects, then path planning accuracy is improved, but processing time increases
Solution Approach 1:
The patent extracts only the critical spatial features needed for path planning from complete evidence grids, removing redundant data about empty spaces and object interiors. This extraction process reduces the computational workload for correlation operations while maintaining the accuracy needed for effective path planning
Solution Approach 2:
The patent applies partial action by processing only the essential portions of evidence grid data that contribute to navigation accuracy. Rather than processing complete grids with all spatial details, the system processes a reduced subset of critical features, achieving sufficient path planning accuracy with reduced processing time
3Reliability
If complete evidence grids are used for correlation, then navigation reliability is improved, but correlation speed decreases
Solution Approach 1:
The patent extracts and retains only the essential features from complete evidence grids that are necessary for reliable correlation-based navigation. By removing redundant data about empty spaces and object interiors, the system achieves faster correlation processing while maintaining navigation reliability through preservation of critical boundary and feature data
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A system is provided for correlating evidence grids. In certain embodiments, the system includes a sensor that generates signals describing a current section of an environment; a memory configured to store measurements of historical sections of the environment; and a processor coupled to the sensor and configured to calculate navigation parameters based on signals received from the sensor. Further, the processor converts the signals received from the sensor into a current evidence grid and removes data from the current evidence grid to form a reduced evidence grid; converts the measurements of historical sections into a historical evidence grid; and correlates the reduced evidence grid with the historical evidence grid by adjusting position and orientation of the reduced evidence grid and the historical evidence grid in relation to one another and calculating correlative values, and searching for a highest correlative value.