Autonomous Mobile Robot Cell Mapping for Cluttered Floor Coverage
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Solution Overview
Problem
Existing autonomous mobile robots, such as robotic vacuum cleaners, face inefficiencies when navigating cluttered floor areas due to unsystematic movement patterns, leading to increased position errors and poor coverage performance.
Innovation Solution
The implementation of a floor covering strategy that involves dividing the floor area into cells with a primary and secondary boundary, where the robot executes initial and additional double strokes to systematically map and cover each cell, using perceptors to detect obstacles and update a topological map for efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a random or simple repetitive movement pattern is employed to achieve coverage of cluttered floor areas, then the robot can navigate obstacles, but the position tracking error gradually increases causing mislocalization
Solution Approach 1:
The floor area is divided into discrete cells with primary and secondary boundaries. The robot systematically navigates through these segmented cells using double-stroke patterns, which provides structured movement that reduces cumulative position errors compared to random navigation while maintaining the ability to handle cluttered environments.
2Productivity
If an excess of movements and covered distance is used to achieve suitable coverage, then the robot can cover all areas, but the position tracking system exhibits gradually increasing position error
Solution Approach 1:
The robot performs preliminary mapping of the floor area to identify cells, boundaries, and obstacles before executing the coverage pattern. This preliminary action allows the robot to plan an efficient systematic path through cells, reducing unnecessary movements and the associated position tracking errors while ensuring complete coverage.
Solution Approach 2:
The robot continuously updates its map and track its position within cells during the double-stroke coverage pattern. This feedback mechanism allows the robot to correct position deviations in real-time, maintaining tracking accuracy even over extended coverage distances.
3Measurement precision
If a systematic cell-by-cell approach is used to reduce position errors, then the robot maintains better localization, but the navigation complexity increases
Solution Approach 1:
The floor area is divided into discrete cells with primary and secondary boundaries. The robot systematically navigates through these segmented cells using double-stroke patterns, which provides structured movement that reduces cumulative position errors compared to random navigation while maintaining the ability to handle cluttered environments.
4Device complexity
If simple coarse cell division is used for mapping, then the robot can maintain simpler data structures, but the coverage efficiency decreases due to unnecessary movements
Solution Approach 1:
The floor area is divided into discrete cells with primary and secondary boundaries. The robot systematically navigates through these segmented cells using double-stroke patterns, which provides structured movement that reduces cumulative position errors compared to random navigation while maintaining the ability to handle cluttered environments.
Solution Approach 2:
The robot performs preliminary mapping of the floor area to identify cells, boundaries, and obstacles before executing the coverage pattern. This preliminary action allows the robot to plan an efficient systematic path through cells, reducing unnecessary movements and the associated position tracking errors while ensuring complete coverage.
Data Source
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Figure 3A~3D
AI summary
An autonomous mobile robot configured to move across a floor area in accordance with a floor covering strategy that includes: • based on a topological map of the floor area, designating a location of a current cell that is bounded by a primary boundary (302); • executing a series of double strokes into and within the current cell, while mapping obstructive objects (306) within the current cell (300) onto an obstacle map; • from said obstacle map determining a secondary boundary (304) of the current cell, which boundary encloses an area (308) of the current cell covered by the executed double strokes, and distinguishes between secondary boundary portions thereof at which an obstructive object (306) is located, and secondary boundary portions thereof at which no obstructive object is located; and • adding the determined secondary boundary (304) to the topological map of the floor area.