Lawn Mowing Robot Path Planning for Irregular Operation Regions
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Solution Overview
Problem
Lawn mowing robots have low operation efficiency due to the complex and varied shapes of their operation regions, which differ from indoor spaces and often feature different ground materials, leading to inefficient movement patterns.
Innovation Solution
A lawn mowing robot with a controller that sets reference lines and divides the operation region into sub-regions using coordinate information, allowing for a preset movement pattern that minimizes unmowed areas and optimizes movement efficiency, while also sensing and adapting to obstacles and gradients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a general moving robot traveling algorithm is used, then the robot can operate in various environments, but the operation efficiency is significantly low in lawn mowing operation regions
Solution Approach 1:
The operation region is divided into multiple sub-regions based on contour lines and gradient information. The controller segments the lawn area into manageable zones, allowing the robot to systematically navigate and mow each section, thereby improving operation efficiency in complex outdoor environments
Solution Approach 2:
The robot adapts its movement pattern to local conditions by detecting gradient directions and contour lines. Different regions with different slopes and shapes receive customized navigation strategies, enabling efficient mowing while adapting to the specific characteristics of each operation region
2Adaptability or versatility
If the robot follows contour lines for movement, then it can adapt to various operation region shapes, but it may get stuck at concave vertices with obtuse angles
Solution Approach 1:
The controller pre-detects concave vertices with obtuse angles in the operation region contour before the robot reaches them. By identifying these problematic points in advance, the system can prepare alternative movement strategies to prevent the robot from getting stuck, ensuring continuous and reliable operation
Solution Approach 2:
Instead of following the contour line strictly at concave vertices with obtuse angles, the robot inverts the approach by moving inward perpendicular to the contour line. This alternative strategy allows the robot to navigate past problematic vertices without getting stuck, maintaining movement reliability
3Productivity
If the robot divides the operation region into sub-regions, then it can optimize movement patterns, but it increases the complexity of control algorithms
Solution Approach 1:
The operation region is divided into multiple sub-regions based on contour lines and gradient information. The controller segments the lawn area into manageable zones, allowing the robot to systematically navigate and mow each section, thereby improving operation efficiency in complex outdoor environments
Solution Approach 2:
The controller pre-processes the operation region map to identify contour lines, gradient directions, and concave vertices before the robot begins mowing. By performing these calculations in advance, the system reduces real-time computational complexity while maintaining optimized movement patterns
Data Source
Figure 1A~1B
Figure 1C~1D
Figure 1E~2
AI summary
A lawn mowing robot includes a body, a driving unit driven such that the body moves within an operation region, and a controller setting first information related to at least one reference line using coordinate information corresponding to vertices included in a polygon forming an operation region and setting second information related to a plurality of regions such that the operation region is divided into the plurality of regions using the first information, wherein the controller controls the driving unit such that the body moves according to a preset movement pattern by the plurality of divided regions using the second information.