Robot Cleaner Sector Mapping for Accurate Position Recognition
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Solution Overview
Problem
Existing robot cleaners face challenges in efficiently mapping and cleaning large areas due to limitations in object detection and position recognition, often relying on expensive sensors and accumulating position errors, which affects their ability to divide regions effectively and maintain accurate navigation.
Innovation Solution
A robot cleaner system that divides the environment into sectors using inexpensive sensors like infrared or supersonic sensors, creates partial maps based on feature lines, and constructs an entire map by compensating for sector orientations and position errors, allowing for precise navigation and cleaning operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive sensors are used for object detection and position recognition, then measurement precision and reliability are improved, but device cost and complexity increase
Solution Approach 1:
The patent divides the cleaning area into multiple sectors and creates partial maps for each sector separately. This segmentation allows the use of simpler sensors within each sector while maintaining overall navigation accuracy through cumulative mapping. The sector-based approach reduces the complexity burden by breaking down the large-scale positioning problem into smaller, manageable units.
Solution Approach 2:
The patent introduces feature lines as intermediary elements extracted from detection data to represent sector boundaries and important features. These feature lines serve as mediators between the simple sensor inputs and the complex navigation requirements, enabling accurate position recognition without directly using expensive sensors. The feature lines act as a simplified representation that bridges the gap between limited sensor capabilities and precise navigation needs.
2Device complexity
If simple and inexpensive sensors are used, then device cost is reduced, but measurement precision and position accuracy deteriorate
Solution Approach 1:
The patent merges multiple detection data points collected within each sector to create a comprehensive partial map. By combining information from infrared or supersonic sensors across multiple positions and angles, the system achieves accurate sector mapping and position recognition despite using simple sensors. The merging of data from multiple sources compensates for the limitations of individual inexpensive sensor readings.
Solution Approach 2:
The patent implements feedback mechanisms where the robot continuously compares detected feature lines with stored partial map information to correct position errors. The system uses the detected objects and feature lines as feedback to verify and adjust its position estimates, enabling accurate navigation even with simple sensors. This feedback loop allows the inexpensive sensor system to achieve precision comparable to more expensive systems through iterative correction.
3Productivity
If the robot cleans large areas continuously, then productivity increases, but position errors accumulate affecting navigation accuracy
Solution Approach 1:
The patent segments the large cleaning area into multiple smaller sectors, each with its own partial map and coordinate system. This segmentation prevents error accumulation by isolating position measurements to local sectors rather than allowing errors to propagate across the entire large area. The robot can accurately navigate within each sector independently, maintaining reliability even when cleaning extends over large total areas.
Solution Approach 2:
The patent uses feature lines as intermediary reference elements that span across sector boundaries. These feature lines serve as stable reference points that help the robot maintain position accuracy when transitioning between sectors. By using these intermediary feature lines as anchors, the system can correct position errors that would otherwise accumulate during continuous large-area cleaning operations.
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
The system enables efficient and accurate cleaning of large areas by using inexpensive sensors to create detailed maps and compensate for position errors, reducing the likelihood of missed regions and enhancing cleaning efficiency and stability.
Implementation Method 1
An inexpensive sensor such as an infrared ray sensor or a supersonic sensor may be used as the detecting device
Implementation Method 2
An inexpensive sensor such as an infrared ray sensor or a supersonic sensor may be used as the detecting device
Data Source
AI summary
A robot cleaner and a method for controlling the same are provided. A region to be cleaned may be divided into a plurality of sectors based on detection data collected by a detecting device, and a partial map for each sector may be generated. A full map of the cleaning region may then be generated based on a position of a partial map with respect to each sector, and a topological relationship between the partial maps. Based on the full map, the robot cleaner may recognize its position, allowing the entire region to be completely cleaned, and allowing the robot cleaner to rapidly move to sectors that have not yet been cleaned.