Mobile Robot Vision Mapping for Closed-Loop Cleaning Paths
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Solution Overview
Problem
Conventional mobile robots lack the ability to recognize their position and may repeatedly clean the same areas, leading to inefficient cleaning processes due to their random movement methods and inability to form closed curved cleaning paths.
Innovation Solution
A method and system for a mobile robot that captures image information at predetermined intervals, extracts feature points, and creates maps by matching these points to compensate for position errors, ensuring the cleaning path forms a closed curved line by dividing the cleaning region into sections and connecting maps to minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a mobile robot uses random movement method, then the robot can move freely without complex control, but the robot cannot recognize its position and repeatedly cleans the same areas
Solution Approach 1:
The patent replaces the mechanical/random movement control system with an optical-based navigation system. The mobile robot uses a camera to capture images and extracts feature points from these images to determine its position and build maps of the environment, substituting random mechanical movement with vision-based intelligent navigation.
Solution Approach 2:
The patent introduces feature points extracted from images as an intermediary between the robot's movement system and its navigation system. These feature points serve as mediators that allow the robot to recognize its position and map the environment without requiring complex direct control mechanisms.
2Device complexity
If the mobile robot does not form closed curved cleaning paths, then the cleaning process is simpler, but the robot cannot accurately map regions and compensate position errors
Solution Approach 1:
The patent implements a feedback mechanism where the robot captures images during cleaning, extracts feature points, and uses these points to build and update maps. The closed curved path ensures that the robot returns to starting positions, allowing it to verify and compensate for position errors through continuous feedback from the mapping process.
Solution Approach 2:
The patent performs preliminary mapping actions by capturing images and extracting feature points before completing the full cleaning cycle. This preliminary action of building maps along closed curved paths enables the robot to pre-calculate position compensations that are then applied during subsequent cleaning operations.
3Productivity
If the mobile robot divides the cleaning region into multiple regions, then the robot can systematically cover the entire area, but the mapping and position compensation process becomes more complex
Solution Approach 1:
The patent divides the cleaning region into multiple sub-regions or cells that the robot systematically visits. By segmenting the environment and using closed curved paths within each segment, the robot can build maps of individual regions and then integrate them into a complete map, making the overall mapping process more manageable and systematic.
Data Source
AI summary
Disclosed is a mobile robot and a controlling method of the same. An entire movement region is divided into a plurality of regions, and a partial map is gradually made by using feature points of a plurality of images of the divided regions. Then, the map is compensated into a closed curved line, thereby making an entire map. Furthermore, when the mobile robot is positioned at a boundary of neighboring regions of the cleaning region, the boundary where a closed curved line is formed, the mobile robot compensates for its position based on a matching result between feature points included in the map, and feature points extracted from images captured during a cleaning process.