Robot Grid Traversal for Complete Lawn Coverage
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Solution Overview
Problem
Existing robot mowers face challenges in achieving high coverage rates and efficiency due to limitations in path tracking accuracy, caused by factors like lawn topography, grass density, and the use of low-performance controllers.
Innovation Solution
A traversal method and system that utilize a grid map divided into working and non-working regions, with the robot traversing in bow-shaped or spiral outward manners within a rectangular coordinate system. The method involves randomly selecting a starting point and preset rule for initial traversal, and adjusting based on remaining working region areas to ensure thorough coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If path tracking control is implemented using GPS, laser, or UWB positioning methods, then the robot can establish a lawn electronic map and perform path planning, but the path tracking accuracy deteriorates due to factors like lawn topography, grass density, and component consistency, resulting in missed mowing
Solution Approach 1:
The lawn area is divided into multiple grid cells forming a grid map, with each cell representing a discrete working unit. This segmentation allows the robot to systematically traverse each cell while maintaining awareness of its position and coverage status, improving both path tracking reliability and overall coverage efficiency
Solution Approach 2:
The system pre-divides the working area into a structured grid map before traversal begins, and pre-plans paths through multiple grid cells. This preliminary organization of the workspace enables the robot to follow predetermined trajectories that account for lawn characteristics, reducing real-time control complexity and improving path tracking accuracy
2Productivity
If a high-performance controller is used to improve path tracking speed and accuracy, then the robot can complete traversal more efficiently, but the cost increases significantly
Solution Approach 1:
The traversal task is divided into multiple sequential grid cell operations rather than requiring continuous high-speed path tracking across the entire lawn. This segmentation allows the use of simpler, lower-cost controllers that can handle discrete navigation decisions between grid cells without needing high-performance real-time control capabilities
Solution Approach 2:
The robot dynamically adjusts its traversal strategy by selecting different grid cells based on coverage status and lawn characteristics. This dynamic adaptation allows the system to optimize performance for each specific segment rather than requiring uniformly high performance across all operations, enabling the use of more cost-effective controllers
3Manufacturing precision
If the robot follows a fixed path to ensure complete coverage, then the coverage rate improves, but the time required for traversal increases
Solution Approach 1:
The system pre-divides the lawn into a grid map and pre-determines traversal sequences through multiple grid cells before the robot begins operation. This preliminary path planning through structured grid cells ensures complete coverage while optimizing the traversal sequence to minimize total traversal time
Solution Approach 2:
The robot dynamically adjusts its traversal path by selecting the next grid cell based on current position, coverage status, and lawn characteristics. This dynamic path selection through the grid map allows the robot to maintain complete coverage while adapting to real-time conditions to optimize traversal efficiency and reduce time loss
Data Source
AI summary
A traversal method and system, a robot, and a readable storage medium are disclosed, wherein the method may include: acquiring a grid map and establishing the rectangular coordinate system covering the grid map; and if traversal is performed for the first time, driving the robot to arrive at the starting point, and driving the robot to, according to a randomly selected preset rule, traverse the working region in which the starting point is located and work synchronously; when it is confirmed that the current preset rule applied to the first traversal cannot continue to be executed, acquiring the area of each independent working region in the remaining working region, if the area of any independent working region is not less than a preset area threshold, selecting any coordinate point as a working start point in the working region the area of which is not less than the preset area threshold, driving the robot to arrive at the working start point, and, starting from the working start point, randomly selecting the preset rule to perform traversal and work synchronously until the areas of all the independent working regions are less than the preset area threshold (S3). The present disclosure beneficially improves the traversal ability and work efficiency of the robot.