Adaptive Region Division Using Virtual Doors for Robot Cleaning Maps
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Solution Overview
Problem
Current region division methods for smart mobile floor sweeping devices divide space into fixed-sized squares, failing to accurately match the actual environment, leading to inefficient cleaning and unsatisfactory cleaning maps.
Innovation Solution
An adaptive region division method and system that uses laser radar data and odometer data to build an environmental map, perform feature extraction, generate virtual doors, and divide regions based on these features, allowing for more precise partitioning of the space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed-size square regions are used for space division, then the region division method is simple and clear, but the generated partitions cannot exactly match the actual environment
Solution Approach 1:
The patent transitions from static fixed-size square regions to dynamic adaptive regions that adjust their size and shape based on environmental features. The region division dynamically adapts to walls, doors, and other structural elements detected by the laser radar, allowing partitions to exactly match the actual environment while maintaining computational efficiency through hierarchical processing.
Solution Approach 2:
The patent applies different region division strategies to different areas of the environment. Instead of uniform square partitions, the system creates locally optimized regions that conform to local environmental characteristics such as wall locations, door positions, and room layouts, achieving both simplicity and accuracy through context-aware partitioning.
2Ease of manufacture
If fixed-size square regions are used for space division, then the region division method is simple and clear, but cleaning efficiency is not high
Solution Approach 1:
The adaptive region division dynamically adjusts partition sizes and shapes to optimize cleaning paths. By creating regions that match actual room boundaries and structural features, the system enables more efficient cleaning trajectories that avoid unnecessary backtracking and improve overall cleaning productivity while maintaining algorithmic simplicity.
Solution Approach 2:
The system performs preliminary environmental mapping and feature extraction before executing the cleaning task. By pre-processing the environment data to identify walls, doors, and room layouts, the system prepares optimized region partitions in advance, allowing the cleaning robot to follow efficient paths without real-time computation delays.
3Ease of manufacture
If fixed-size square regions are used for space division, then the region division method is simple and clear, but the obtained cleaning map is not beautiful enough
Solution Approach 1:
The patent creates cleaning maps with varying partition densities and shapes according to local environmental requirements. Regions are locally optimized to match room boundaries, doorways, and structural features, producing aesthetically pleasing and accurate cleaning maps that reflect the true layout of the environment while maintaining overall method simplicity.
Data Source
AI summary
An adaptive region division method and system are provided. The adaptive region division method includes: building an environmental map based on laser radar data and odometer data, to determine information about an environment in which a target device is located (S11); performing feature extraction according to the laser radar data, to determine feature data, where the feature data includes line feature data and point feature data (S12); generating a virtual door according to the feature data and the information about the environment in which the target device is located (S13); and dividing a to-be-divided region where the target device is located according to the virtual door (S14). Therefore, a virtual door is generated according to laser data of a current environment to achieve the purpose of adaptive region division, so that the target device can more efficiently and quickly cover the whole space.