Hierarchical Path Planning for Obstacle-Aware Movement Control
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Solution Overview
Problem
Existing methods for controlling the movement of autonomous devices, such as drones and driverless vehicles, face challenges in efficiently processing large areas with obstacles, leading to latency and overhead issues due to high memory requirements and complex path planning algorithms.
Innovation Solution
The approach involves dividing the controlled area into smaller patterns, using a path finding algorithm to determine movement paths within these patterns, and combining them with external path information to optimize route planning, allowing for efficient navigation around obstacles and reducing memory usage by applying different algorithms based on zoom levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path finding algorithms are applied to entire large areas, then complete path planning coverage is achieved, but processing time and memory consumption increase significantly
Solution Approach 1:
The patent divides the large controlled area into multiple smaller sector patterns, each covering a specific geographic region. Instead of applying path finding algorithms to the entire area, the system processes only relevant sectors containing obstacles or no-fly zones. This segmentation reduces the computational scope from the whole area to localized regions, significantly decreasing processing time while maintaining complete path planning coverage through systematic sector evaluation.
2Reliability
If path finding algorithms are applied to entire large areas, then complete path planning coverage is achieved, but memory capacity requirements increase
Solution Approach 1:
By segmenting the area into discrete sector patterns with defined boundaries and characteristics, the system stores information about obstacles and no-fly zones only within relevant sectors rather than maintaining data structures for the entire large area. This reduces memory capacity requirements as only sectors containing relevant features need detailed processing and storage.
Solution Approach 2:
The patent applies different processing approaches to different sectors based on their local characteristics. Sectors containing obstacles or no-fly zones receive detailed path finding algorithm processing, while empty sectors are handled more simply. This local quality approach ensures complete path planning coverage is achieved only where necessary, optimizing memory usage by avoiding uniform high-resolution processing across the entire area.
3Productivity
If path finding algorithms are selectively applied to specific patterns with obstacles, then processing efficiency improves, but path planning complexity increases
Solution Approach 1:
The system performs preliminary evaluation of sector patterns to identify which sectors contain obstacles or no-fly zones before applying path finding algorithms. This preliminary action filters out empty sectors that don't require complex processing, allowing the system to selectively apply algorithms only to relevant sectors. The preliminary sector identification step simplifies the overall process by avoiding unnecessary algorithm execution in empty areas.
Data Source
AI summary
Apparatuses and methods for movement control of a device are disclosed. The apparatus comprises memory for storing information of patterns covering sectors of the area indicating whether the patterns have at least one item relevant to movement in the area. The information has been configured based on determination of at least one pattern that has at least one item relevant to movement in the area, division of the determined at least one pattern into smaller patterns, determination of at least one of the smaller patterns with at least one item relevant to movement in the area, and repeat of the division until predefined smallest pattern size is reached. A processor is configured to determine whether a search path between first and second locations extends through at least one pattern having at least one item relevant to movement in the area, and to selectively use a path finding algorithm to determine a path of movement within at least one pattern with relevant items through which the search path is determined to extend.