Hierarchical Path Calculation for Open-Environment Navigation
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Solution Overview
Problem
Existing pathfinding methods are inefficient and time-consuming for calculating paths in open environments like large buildings due to the complexity of numerous possible trajectories and the need for detailed cell modeling, which is not well-suited by traditional shortest path algorithms.
Innovation Solution
A method involving the generation of two maps: a first map divided into convex polygonal zones and a second map with fewer, larger zones, using graph algorithms to calculate a provisional path, followed by a more detailed partial path adjustment based on real-time entity positions, reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional shortest path algorithms are used in open environments with detailed cell modeling, then path accuracy is improved, but computation time increases significantly
Solution Approach 1:
The environment is divided into two distinct map representations: a first map with fine-grained cell-level detail for accurate path calculation, and a second map with aggregated super-cells for rapid exploration. This segmentation allows the algorithm to work at different levels of detail appropriately, reducing overall computation time while maintaining path accuracy.
Solution Approach 2:
The invention introduces a hierarchical dimension to the pathfinding problem by creating multiple levels of map abstraction. The second map aggregates multiple first-map cells into super-cells, adding a macro-level view that enables faster initial path exploration before refining details at the micro-level using the first map.
2Measurement precision
If the environment is modeled with a large number of cells to capture all possible trajectories in open environments, then path accuracy is improved, but graph complexity increases
Solution Approach 1:
Multiple adjacent cells from the first map are merged to form super-cells in the second map. This merging reduces the total number of nodes in the graph from the fine-grained cell level to a coarser super-cell level, significantly reducing graph complexity while preserving the essential connectivity and trajectory information needed for accurate pathfinding.
3Measurement precision
If fine-grained cell modeling is used to model all possible movement trajectories, then path accuracy is improved, but the number of graph nodes and edges increases
Solution Approach 1:
The graph structure is segmented into two hierarchical levels: a detailed level (first map) with individual cells and a simplified level (second map) with super-cells. This segmentation allows the algorithm to perform initial path exploration on the simplified graph with fewer elements, then refine the path using the detailed graph only where necessary, reducing the total number of graph elements that must be processed.
Solution Approach 2:
The invention adds a hierarchical dimension to the graph structure, creating a macro-level super-cell graph that aggregates micro-level cell details. This dimensional change enables the system to work with a reduced set of graph elements at the appropriate level of abstraction, decreasing computational complexity while maintaining the ability to capture all necessary movement trajectories when needed.
Data Source
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AI summary
The invention relates to a method for calculating a path in an environment that is intended to be navigated by an entity (T), comprising steps of generating a first map (200) of the environment, divided into a set of first cells (205), generating a second map, divided into second cells, the total number of second cells being strictly lower than the total number of first cells (205), determining, from the second map, a first graph, calculating, from the first graph, a provisional path, determining a region of the first map including an estimated position of the entity (T), generating, from the first map, a second graph, calculating, from the second graph, a partial path between the estimated position and an intersection between the provisional path and a perimeter of the region (260), and moving the estimated position along the partial path.