Closed-Space Map Boundary Profiling for Accurate Zone Division
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for processing maps of closed spaces by mobile devices are inefficient in accurately dividing the space into zones, limiting their operational scope and task execution efficiency.
Innovation Solution
A method that involves obtaining self-locations and obstacle locations, determining a boundary profile and self-circle, and processing the map based on an outer profile to recognize and divide zones accurately, allowing for customized task execution and expanded application scope.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to process maps of closed spaces, then the processing can be completed, but the zone division accuracy is insufficient and task execution efficiency is limited
Solution Approach 1:
The patent segments the closed space into multiple zones by dividing the map into distinct regions with different obstacle characteristics. Each zone is identified and processed independently, enabling accurate spatial differentiation and improving both zone division accuracy and task execution efficiency by allowing targeted operations in specific areas.
Solution Approach 2:
The patent introduces a new dimension of analysis by creating an outer profile representation of the map that goes beyond traditional 2D grid processing. This outer profile dimension captures boundary characteristics and obstacle distributions more effectively, enabling more accurate zone division while improving processing efficiency for task execution.
2Adaptability or versatility
If the mobile device operates in a limited work zone, then it can execute tasks autonomously, but the application scope is restricted
Solution Approach 1:
The patent creates a universal map processing method that can be applied across different closed space environments and mobile device types. The outer profile-based zone division approach is adaptable to various work zones and task requirements, expanding application scope while maintaining autonomous operation capability through standardized processing routines.
Solution Approach 2:
The patent changes the processing parameters from traditional grid-based methods to outer profile-based methods, allowing the system to adapt to different space configurations and task requirements. This parameter change enables the mobile device to operate autonomously across diverse environments, expanding application scope without compromising ease of operation.
3Measurement precision
If boundary recognition and clustering are performed on map information, then zone division basis can be obtained, but the conventional methods cannot achieve accurate closed space division directly
Solution Approach 1:
The patent extracts the essential boundary characteristics from the map by creating an outer profile representation. This extraction process isolates the key geometric features needed for zone division, achieving accurate space division while reducing processing complexity by focusing only on the most relevant map features rather than processing all detailed information.
Solution Approach 2:
The patent performs preliminary processing to create the outer profile representation before conducting zone division. This preliminary action prepares the map data in an optimized format that facilitates accurate and efficient zone division, reducing the complexity of subsequent processing steps while maintaining high division accuracy.
Data Source
AI summary
A method for processing a map of a closed space is provided. The method includes obtaining a plurality of self-locations of a mobile device. The method also includes obtaining a plurality of obstacle locations. The method also includes obtaining a boundary profile based on the obstacle locations, the boundary profile being a closed line formed by sequentially connecting multiple adjacent obstacle locations. The method also includes obtaining a self-circle based on the self-locations of the mobile device, the self-circle being a closed line formed by sequentially connecting multiple adjacent self-location of the mobile device. The method also includes determining the boundary profile as an outer profile when the boundary profile encircles the self-circle at an outer side of the self-circle. The method further includes processing the map of the closed space based on the outer profile.