Zone Cleaning Robot Navigation Using Virtual Maps and LIDAR SLAM
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Solution Overview
Problem
Current cleaning robots lack advanced navigation capabilities to efficiently clean specific areas and adapt to different zones and schedules, often requiring manual intervention and limited flexibility in handling obstacles and floor changes.
Innovation Solution
A system that allows users to define virtual zones on a map, which are transmitted to the robot, enabling it to determine paths, schedules, and adjust boundaries automatically, using LIDAR and SLAM technology for navigation and obstacle avoidance, and allowing for different cleaning modes and schedules based on zone types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cleaning robots use basic navigation to clean specified areas, then they can perform routine cleaning tasks, but they lack the ability to efficiently navigate to and clean specific zones or adapt to different floor plans and schedules
Solution Approach 1:
The patent divides the cleaning area into multiple virtual zones that can be independently defined, scheduled, and cleaned. Each zone can have its own cleaning parameters, schedule, and priority level. This segmentation allows the robot to selectively clean specific areas rather than requiring full-area cleaning, improving adaptability while managing complexity through modular zone management.
Solution Approach 2:
The patent introduces a virtual mapping dimension by creating digital representations of physical spaces with defined zones, boundaries, and coordinates. This virtual layer allows the robot to navigate and clean specific areas without physically marking the environment, adding a software-based dimension that enhances adaptability without proportionally increasing hardware complexity.
2Productivity
If cleaning robots clean entire areas, then they provide comprehensive cleaning coverage, but they waste time and energy cleaning areas that are not needed or already clean
Solution Approach 1:
The patent implements partial cleaning by allowing users to define specific zones within the overall cleaning area. The robot can clean only the necessary portions of the environment based on zone definitions, cleaning schedules, and priority levels. This partial action approach eliminates time spent cleaning already-clean areas or low-priority zones, directly improving productivity while reducing time loss.
Solution Approach 2:
The patent introduces scheduled cleaning operations where different zones can be cleaned at different times and frequencies. High-traffic areas can be cleaned more frequently while low-traffic areas are cleaned less often. This periodic action optimizes cleaning efficiency by matching cleaning frequency to actual need, reducing unnecessary cleaning time and energy consumption.
3Manufacturing precision
If cleaning robots use manual intervention for zone definition, then users can precisely control cleaning areas, but the process requires significant user time and effort
Solution Approach 1:
The patent implements preliminary mapping where the robot autonomously creates a digital map of the environment before zone definition. This pre-established spatial framework provides accurate boundaries, walls, and navigable areas, which serves as a foundation for subsequent zone definition. This preliminary action reduces user effort by eliminating the need for manual boundary measurement while maintaining precision through the robot's own spatial understanding.
Solution Approach 2:
The patent uses virtual copying by creating digital representations of physical zones on the mapped environment. Users define zones by selecting areas on the digital map rather than physically measuring and marking spaces. This copying approach maintains precise zone definition through coordinate-based boundaries while significantly reducing user effort by eliminating physical measurement and marking tasks.
4Adaptability or versatility
If cleaning robots lack floor detection capability, then the system is simpler, but the robot cannot determine which floor plan it is on or access floor-specific zones
Solution Approach 1:
The patent introduces an intermediary mapping system that creates virtual representations of multiple floor plans. The robot uses this digital map intermediary to understand and navigate different floors without requiring complex physical sensors for floor detection. The virtual map serves as a mediator between the robot's navigation system and the physical multi-floor environment, enabling floor-specific zone cleaning while managing complexity through software-based floor identification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and adaptive cleaning by allowing robots to navigate and clean specific areas, adjust to different zones, and handle obstacles, improving user control and operational efficiency.
Implementation Method 1
using LIDAR and SLAM technology for navigation and obstacle avoidance
Implementation Method 2
using LIDAR and SLAM technology for navigation and obstacle avoidance
Data Source
AI summary
In one embodiment, a user indicates one or more virtual zones on an area map on a user device for a particular robot. The zones are then transferred to the robot. The robot determines an optimum order for multiple zones and a path for navigating to the different zones.