Robot Map Region Optimization for Inaccessible Area Removal
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Solution Overview
Problem
Existing map building technologies for intelligent robots often result in inaccurate maps due to non-existent or inaccessible regions, affecting the robot's working efficiency and user experience.
Innovation Solution
A map processing method that identifies and optimizes target regions such as narrow, overflow, and isolated regions by adjusting pixel points to unknown points, using threshold-based criteria and boundary extension techniques to enhance map accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map building is performed using conventional sensor data processing, then the robot can navigate and perform tasks, but the generated map contains non-existent or inaccessible regions resulting in poor accuracy
Solution Approach 1:
The map is segmented into multiple types of regions (accessible regions, narrow regions, isolated regions, overflow regions) based on their characteristics. This segmentation allows targeted processing of different region types to improve overall map accuracy without requiring complete reconstruction of the entire map.
Solution Approach 2:
Different processing strategies are applied to different regions of the map based on their local characteristics. For example, narrow regions are identified and marked as inaccessible, isolated regions are detected and handled separately, and overflow regions are processed to remove false accessible areas. This local quality approach improves map accuracy where needed without uniformly increasing complexity across the entire system.
2Productivity
If the robot uses the generated map for navigation and work, then tasks can be completed, but the presence of inaccessible regions in the map causes poor user experience and reduced working efficiency
Solution Approach 1:
The map processing method performs preliminary identification and correction of problematic regions (narrow, isolated, overflow regions) before the robot uses the map for navigation and task execution. By preprocessing the map to remove inaccessible regions and correct errors, the system ensures higher reliability is established beforehand, preventing navigation failures and improving working efficiency during actual operation.
Data Source
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AI summary
A map processing method, a map processing apparatus, a computer readable storage medium, and an electronic device. The method comprises: acquiring a map image, the map image being used for representing a movable area of a movable object (S110); identifying from the map image a target area having a preset feature(S120); and performing map optimization processing on the target area (S130). The method can process maps, thereby improving the accuracy and attractiveness.