Hierarchical Block-Cell Path Search for Mobile Objects
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Solution Overview
Problem
Existing path search algorithms, such as A* and its variants, face significant computational challenges when dealing with large-sized grid maps, leading to increased search time and difficulty in real-time path adjustments due to map size growth and incomplete map information.
Innovation Solution
The method involves converting a grid map into a block-based map by merging cells and preprocessing the map to extend blocked regions, allowing for efficient block path search and subsequent cell-based path optimization, reducing search time and enabling real-time path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If A* algorithm is used to ensure optimal path finding, then path optimality is improved, but search time increases by geometric progression with map size
Solution Approach 1:
The patent divides the large grid map into multiple blocks, where each block is further divided into cells. Path search is first performed at the block level to obtain a rough path, then refined at the cell level only along the block path. This hierarchical segmentation reduces the search space from the entire map to a subset of blocks and their constituent cells, thereby maintaining path optimality while significantly reducing search time that would otherwise increase geometrically with map size.
2Area of stationary object
If map size increases to cover larger areas, then coverage area is improved, but search time increases by geometric progression
Solution Approach 1:
The patent segments the large coverage area into multiple blocks, allowing the system to handle arbitrarily large maps by dividing them into manageable units. The hierarchical search approach (block level followed by cell level) ensures that search time does not increase geometrically with the total map area, as the search is confined to relevant blocks and their cells rather than the entire map.
Solution Approach 2:
The patent introduces a hierarchical dimension to the path search process by operating at two levels: block level and cell level. This dimensional hierarchy transforms the search problem from a single-level exhaustive search across the entire map to a multi-level search that progresses from coarse to fine granularity, thereby decoupling search time from geometric progression with map size.
3Adaptability or versatility
If real-time path adjustment is required due to mobile obstacles or incomplete map information, then adaptability is improved, but search time must be reduced
Solution Approach 1:
The hierarchical block-cell structure enables efficient real-time path adjustments by allowing quick re-planning at the block level when obstacles are detected. Since the search is already organized in a hierarchical manner, re-computing paths when map information changes or mobile obstacles appear requires searching only the affected blocks and their cells, significantly reducing the time penalty compared to re-searching the entire map.
4Productivity
If D* algorithm is used for dynamic path changes, then path reuse efficiency is improved, but new path search is still required when destination changes
Solution Approach 1:
The hierarchical block-cell structure naturally supports destination changes by allowing the block path search to quickly adapt to new destinations. When the destination changes, the system performs block-level path search from the current position to the new destination, then refines only the relevant cell paths. This segmented approach is more versatile than D* algorithm for destination changes, as it doesn't require complete path re-computation while maintaining efficiency.
Data Source
AI summary
A path search method of a mobile object in a grid map having a plurality of cells, each having an identical size, is provided. The path search method includes: generating a block map having a plurality of blocks by merging a specific number of cells in the grid map; obtaining a block path by finding a path from a starting position to a destination position in the block map; and obtaining a final path of the mobile object by performing a cell-based path search on cells in the blocks on the block path.