Pool Edge Mapping for Closed-Loop Cleaning Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automatic pool cleaning devices face issues with inaccurate map-building due to insufficient positioning accuracy and cumulative errors, leading to an incomplete closed-loop map, which prevents the technical solution, thereby preventing the generation of closed-loop map, which prevents the generation of a closed-loop map, which prevents the generation of a closed-loop map, which prevents the generation of a closed-loop map, which prevents the generation of a closed-loop map, which results in the generation of a closed-loop map, which causes inaccurate path planning and navigation.
Innovation Solution
A map-building method for automatic pool cleaning devices that involves traveling along the pool edge, collecting data for a first path, and generating a closed-loop map by optimizing point cloud data using a second path to correct deviations and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If map-building is performed by traveling along the pool edge for one circle, then the mapping task is completed, but the built map cannot be a closed map due to insufficient positioning accuracy and cumulated errors
Solution Approach 1:
The system performs preliminary actions by collecting point cloud data multiple times along the pool edge before generating the final map. Instead of completing the mapping task in a single circle, the device accumulates data from multiple passes and uses optimization algorithms to close the map loop, thereby resolving the contradiction between mapping efficiency and map closing accuracy.
2Loss of information
If the automatic pool cleaning device travels along the pool edge to build a map, then pool edge information is collected, but positioning inaccuracies and cumulative errors prevent the starting point from connecting with the ending point
Solution Approach 1:
The system implements feedback by continuously optimizing the point cloud data collected during multiple passes along the pool edge. The optimization process uses the accumulated position information to adjust and correct cumulative errors, ensuring that the starting point connects with the ending point to form a closed map loop.
3Quantity of substance
If point cloud data is collected during travel along the pool edge, then pool edge information is obtained, but the data contains deviations that prevent closed-loop map generation
Solution Approach 1:
The system applies partial or excessive action by collecting point cloud data multiple times beyond what would be required for a single mapping pass. This excessive data collection provides redundant information that can be optimized to correct deviations and achieve closed-loop map generation, resolving the contradiction between data quantity and map closure precision.
Data Source
AI summary
The present disclosure provides a map-building method for an automatic pool cleaning device, comprising: controlling the automatic pool cleaning device to travel one circle or longer than one circle along a pool edge on a pool bottom or a water surface, and during the travel along pool edge, collecting pool edge information in real-time to obtain point cloud data for a first path, wherein a path of the travel along the pool edge is the first path; controlling the automatic pool cleaning device to continue traveling along the pool edge from an ending point of the first path and continue to collect pool edge information in real time until a first predetermined condition is met, thereby obtaining point cloud data for a second path, wherein a path along the pool edge starting from the ending point of the first path is the second path; and generating a closed pool-edge map.