Cleaning Robot Region Division for Dynamic Passage Handling
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Solution Overview
Problem
Cleaning robots face inefficiencies due to poor adaptability in dynamic environments, leading to repeated sweeping and missed areas, as they rely on static maps that fail to account for changes in the environment.
Innovation Solution
Implementing a dynamic region division method that uses real-time environment information to identify passage structures and block or open passages, ensuring that each region is fully cleaned before moving on to the next, utilizing sensors like laser sensors and vision systems for accurate mapping and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a cleaning robot uses a static cleaning map for region division, then the device complexity is reduced and ease of operation is improved, but the adaptability to changing environments deteriorates and cleaning efficiency decreases due to repeated sweeping and missed areas
Solution Approach 1:
The patent applies dynamics by transforming the static cleaning map into a dynamic region division system. The robot continuously updates region boundaries and passage identifications based on real-time environmental information and cleaning progress. Region divisions are adjusted dynamically as the robot cleans, allowing adaptation to environmental changes while maintaining systematic control through coordinate-based boundary representations and passage structure databases.
2Productivity
If the robot divides the cleaning area into multiple regions using a static map, then the productivity is improved through systematic cleaning, but the loss of time increases due to repeated sweeping and missed areas when environment changes
Solution Approach 1:
The patent implements feedback mechanisms where the robot continuously monitors cleaning progress within each region and uses this information to adjust its cleaning path and region boundaries. The system receives feedback from sensors about environmental changes and cleaning status, then updates the region division and passage identification accordingly, preventing repeated sweeping and missed areas by adapting to actual cleaning completion status in real-time.
Solution Approach 2:
The patent applies preliminary action by pre-identifying passage structures and potential region boundaries during the mapping phase, storing this information in a database. This preliminary identification of passages and regions allows the robot to plan cleaning paths in advance while maintaining the flexibility to adjust region divisions during actual cleaning based on real-time feedback, thus improving productivity without excessive time loss.
3Measurement precision
If the robot relies on historical map data for navigation, then the measurement precision of environment mapping is reduced, but the loss of information is minimized by using existing data
Solution Approach 1:
The patent applies dynamics by continuously updating the environment map with real-time sensor data during cleaning operations. The system maintains a database of passage structures and region boundaries that is dynamically refined as the robot collects new environmental information. This dynamic updating process ensures both high measurement precision through continuous sensor feedback and minimizes information loss by integrating historical map data with real-time observations.
Data Source
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AI summary
Provided are dynamic region division and region passage identification methods and a cleaning robot. The dynamic region division method includes: acquiring environment information collected by a robot when working in a first region; determining whether the robot has completed a work task in the first region, when a presence of a passage entering a second region is determined based on the environment information; and complementing a boundary at the passage to block the passage, when the work task is not completed. According to the technical solution provided by the embodiment of the present application, the occurrence probability of repeated sweeping and miss sweeping is reduced, and the cleaning efficiency is high. In addition, the technical solution provided by the embodiment of the present application relies on the environment information collected during the work, rather than relying on historical map data, so that the environmental adaptability is high.