Mobile Robot Area Segmentation for Predictable Coverage Sequencing
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Solution Overview
Problem
Autonomous robots lack predictability and user control in their mission operations, as users have limited understanding of the areas being covered and no input regarding the mission, leading to unpredictable behavior.
Innovation Solution
A computing device generates a segmentation map based on occupancy data collected by a mobile robot, classifying areas as non-clutter and clutter, and computes a coverage pattern for navigation, allowing the robot to sequentially traverse these areas in a defined sequence, which can be modified by user input for specific cleaning levels or boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the robot operates autonomously without user input, then the robot can perform tasks independently, but the user lacks understanding and control regarding the robot's mission and area coverage
Solution Approach 1:
The system provides visual feedback to the user through a graphical user interface that displays the segmentation map and coverage pattern. The user can see the defined areas, the sequence in which they will be cleaned, and the robot's current progress, thereby maintaining autonomous operation while eliminating information loss.
Solution Approach 2:
A computing device acts as an intermediary between the user and the robot. It generates the segmentation map, computes the coverage pattern, and communicates this information to the user through a graphical interface, bridging the gap between autonomous operation and user understanding.
2Productivity
If the robot cleans all areas uniformly, then complete coverage is achieved, but efficiency is reduced due to unnecessary cleaning of already clean areas
Solution Approach 1:
The system divides the cleaning environment into multiple segments and identifies specific sub-regions that require cleaning. Instead of uniform cleaning, the robot applies cleaning operations only to the identified sub-regions within each segment, achieving both efficiency and completeness.
Solution Approach 2:
The cleaning area is segmented into multiple regions, and each region is further analyzed to identify specific sub-regions requiring cleaning. This hierarchical segmentation allows the robot to efficiently target only the necessary areas while maintaining complete coverage of all required zones.
3Stability of the object's composition
If the robot follows a fixed cleaning pattern, then the operation is predictable, but adaptability to different area configurations is reduced
Solution Approach 1:
The coverage pattern is dynamically generated based on the specific segmentation map and cleaning requirements. The system computes an optimized sequence that adapts to the particular configuration of areas and sub-regions, providing both predictability through systematic sequencing and adaptability to different layouts.
Solution Approach 2:
The system changes the parameters of the cleaning operation based on the identified sub-regions and area configurations. The coverage pattern adjusts parameters such as cleaning sequence, direction, and priority levels to match the specific environmental configuration while maintaining a systematic and predictable approach.
Data Source
AI summary
A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.