Pool-Cleaning Robot Path Planning for Full Bottom Coverage
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Solution Overview
Problem
Manual cleaning of pools is inefficient and requires significant human resources due to the large size of the pool.
Innovation Solution
A method for controlling a robot to move by constructing a contour map of the pool bottom, performing path planning based on this map to generate round-trip parallel paths, and controlling the robot to clean the pool along these paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual cleaning is used, then the pool can be cleaned, but the cleaning efficiency is low and requires significant human resources
Solution Approach 1:
The pool cleaning robot performs cleaning operations autonomously without human intervention. It navigates the pool bottom independently, detects obstacles, and executes cleaning tasks automatically, transforming the cleaning process into a self-service operation that eliminates manual labor and significantly improves cleaning efficiency while reducing time consumption
Solution Approach 2:
The patent replaces the manual mechanical cleaning system with an automated robotic system equipped with sensors, processors, and motorized components. The robot uses electronic control systems to navigate and clean the pool, substituting human physical labor with an integrated mechanical-electronic system that operates autonomously and efficiently
2Area of stationary object
If the robot follows a simple path, then the control is simple, but the coverage of the pool bottom is incomplete
Solution Approach 1:
The path planning is segmented into multiple parallel trajectories that systematically cover different regions of the pool bottom. The cleaning path is divided into multiple passes with specific spacing, ensuring complete coverage of the entire pool area. This segmentation approach allows the robot to methodically traverse the full coverage area while maintaining manageable control complexity through structured path segments
Solution Approach 2:
The path planning transitions from simple linear motion to two-dimensional coverage patterns by introducing parallel trajectories at different positions across the pool width. This dimensional expansion enables complete area coverage by utilizing both longitudinal and lateral dimensions of movement, ensuring the entire pool bottom is covered while maintaining systematic and controllable path structures
3Speed
If the robot moves quickly, then the cleaning speed is high, but the cleaning quality may be compromised
Solution Approach 1:
The robot implements dynamic speed adjustment capabilities that allow it to vary its movement speed based on real-time conditions. The control system can accelerate during open-water traversal and decelerate when approaching obstacles or during critical cleaning operations, optimizing the balance between overall cleaning speed and localized cleaning quality through adaptive velocity modulation
Data Source
AI summary
Embodiments of this application provide a method for controlling a robot to move. The method includes: constructing a contour map of a bottom of a target pool based on edge information of the bottom of the target pool; performing path planning on the bottom of the target pool based on the contour map to obtain a planned path for the bottom of the target pool, where the planned path for the bottom of the target pool includes a plurality of round-trip parallel paths, and the planned path for the bottom of the target pool covers the bottom of the target pool; and controlling the robot to move along the planned path and clean the bottom of the target pool in a moving process. According to this application, a problem of low efficiency in manually cleaning a pool can be resolved, and pool cleaning efficiency can be improved.