Mobile Robot Area Segmentation for Predictable Coverage Patterns
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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 they will cover and no input regarding the mission specifics.
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.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous robots perform missions independently without user input, then automation extent is improved, but user understanding and control over mission operations deteriorates
Solution Approach 1:
The system provides visual feedback to users through a user interface that displays the segmentation map and coverage pattern. Users can view the defined regions, sub-regions (clutter and non-clutter areas), and the planned navigation sequence before the robot executes the mission. This feedback loop maintains automation while improving user understanding and control.
2Productivity
If robots navigate surfaces systematically to improve cleaning efficiency, then productivity is improved, but device complexity increases due to segmentation and pattern computation
Solution Approach 1:
The surface is divided into defined regions and further segmented into sub-regions (clutter and non-clutter areas) within each region. This segmentation enables systematic navigation patterns that improve cleaning efficiency by organizing the cleaning task into manageable sequences while the computation is handled by the processor.
3Productivity
If robots classify areas into clutter and non-clutter sub-regions to optimize navigation sequence, then cleaning efficiency is improved, but measurement precision requirements increase for accurate area classification
Solution Approach 1:
The system changes the parameter of navigation by computing different coverage patterns based on the classified sub-regions. The processor analyzes the segmented areas and generates optimized navigation sequences that account for clutter and non-clutter regions, improving cleaning efficiency without requiring extreme measurement precision.
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.