Cleaning path planning method based on pathfinding cost, chip, and cleaning robot
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cleaning robots often repeat cleaning certain areas while missing others, leading to inefficient path planning and prolonged cleaning times due to issues with global coverage and the inability to distinguish between cleaned and uncleaned areas, affecting user experience.
Innovation Solution
A cleaning path planning method that divides the cleaning area into sub-blocks using cleaning lines and obstacle boundaries, planning bow-shaped paths within each sub-block, and optimizing pathfinding costs to ensure efficient traversal and minimize repeated navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global coverage cleaning is performed in the cleaning area, then all areas can be covered, but the robot repeatedly cleans some areas while missing others, reducing cleaning efficiency
Solution Approach 1:
The cleaning area is divided into multiple sub-blocks with clear boundaries. The robot plans and executes cleaning for each sub-block separately, tracking the cleaning status of individual sub-blocks. This segmentation eliminates the problem of repeated cleaning in some areas while missing others, ensuring complete and efficient coverage.
2Ease of operation
If the robot plans paths between working areas, then navigation is achieved, but path planning time increases, reducing response speed
Solution Approach 1:
The robot pre-calculates and stores optimal paths between different sub-blocks before actual cleaning operations. When moving from one sub-block to another, the robot directly retrieves the pre-planned path rather than computing it in real-time, significantly reducing path planning time while maintaining navigation accuracy.
3Reliability
If cleaning lines are configured and sub-blocks are divided, then cleaning coverage is improved, but pathfinding complexity increases
Solution Approach 1:
The cleaning area is divided into multiple sub-blocks with clear boundaries. The robot plans and executes cleaning for each sub-block separately, tracking the cleaning status of individual sub-blocks. This segmentation simplifies the overall pathfinding problem by breaking it into smaller, manageable sub-problems.
Solution Approach 2:
Different pathfinding strategies are applied to different sub-blocks based on their specific characteristics. The robot adjusts its cleaning path within each sub-block according to local conditions such as obstacle distribution and sub-block shape, rather than using a single uniform approach for the entire cleaning area.
Data Source
AI summary
Disclosed are a cleaning path planning method based on a pathfinding cost, a chip, and a cleaning robot. The method includes step 1, configuring cleaning lines in a map matching a cleaning area according to map boundaries and obstacle boundaries in different directions in the cleaning area of a mobile robot; step 2, setting a candidate entrance/exit satisfying a preset pathfinding cost condition and found in a current non-cleaned sub-block by the mobile robot at a current position as a cleaning entrance position of the current non-cleaned sub-block; step 3, controlling the mobile robot to move to the cleaning entrance position of the current non-cleaned sub-block; step 4, searching for and planning a cleaning entrance position and a cleaning termination position of a next non-cleaned sub-block by repeating steps 2-3 described above in a case of the mobile robot moves to the cleaning termination position of the current non-cleaned sub-block.