Lawn Mower Path Angle Planning for High-Coverage Mowing
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Solution Overview
Problem
Current path planning methods for intelligent lawn mowers are inefficient, prone to repetitive mowing, and require significant hardware resources, making them unsuitable for large-scale applications and complex environments like golf courses.
Innovation Solution
A path planning method and system that utilizes a touch panel interface for user input to set a path angle, adjusting the path planning based on a preset algorithm, allowing for optimal traversal of the mowing region by segmenting and connecting sub-regions, and providing a self-defined mowing direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SLAM-based path planning method is used, then coverage rate is improved, but operation time increases and hardware resource consumption increases
Solution Approach 1:
The patent divides the mowing region into multiple sub-regions and processes them sequentially. The controller segments the overall path planning task into smaller manageable sections, allowing the lawn mower to complete coverage of each sub-region before moving to the next, thereby reducing total operation time while maintaining high coverage rate.
Solution Approach 2:
The patent pre-calculates and stores optimal path planning data for different sub-regions before actual mowing operations. The controller has access to pre-computed path information, which eliminates the need for real-time complex calculations during mowing, significantly reducing operation time while ensuring complete coverage.
2Reliability
If SLAM-based path planning method is used, then coverage rate is improved, but hardware resource consumption increases
Solution Approach 1:
The patent segments the path planning task into discrete sub-region processing steps, allowing the controller to use simple computational logic for each segment rather than requiring complex SLAM algorithms. This reduces hardware resource consumption while achieving complete coverage through systematic sub-region traversal.
Solution Approach 2:
The patent uses lightweight, low-cost computational approaches for path planning instead of resource-intensive SLAM algorithms. The controller implements simple path planning logic that consumes minimal hardware resources, achieving effective coverage without requiring expensive or power-intensive computational hardware.
3Device complexity
If artificial potential field method is used, then device complexity is reduced, but productivity decreases due to local optimum and repeated mowing
Solution Approach 1:
The patent divides the mowing region into multiple sub-regions and processes them in a systematic sequence. This segmentation prevents the lawn mower from getting trapped in local optima by ensuring complete coverage of each sub-region before moving to the next, thereby maintaining high productivity without requiring complex global optimization algorithms.
Solution Approach 2:
The patent pre-defines the sequence and boundaries of sub-regions before mowing operations begin. This preliminary organization of the work space allows the simple artificial potential field method to operate efficiently within each predefined region without repeatedly revisiting areas, thus maintaining both low device complexity and high productivity.
4Adaptability or versatility
If stochastic planning algorithm is used, then adaptability is improved, but productivity decreases due to low efficiency and repeated cleaning
Solution Approach 1:
The patent segments the mowing task into systematic sub-region processing steps, providing adaptability to handle different region shapes and sizes while maintaining high productivity. Each sub-region is processed completely before moving to the next, eliminating repeated cleaning and improving efficiency compared to stochastic approaches.
Data Source
AI summary
The present disclosure relates to the field of intelligent lawn mowers and logic control technologies thereof, and discloses a path planning method for an intelligent lawn mower. The path planning method includes: starting a touch panel of the intelligent lawn mower; entering a path planning setting interface, which displays a schematic diagram of a region to be mowed, a path angle indicating image and a path angle setting image; receiving a touch input of a user with respect to the path angle setting image to set a path angle; adjusting, based on the set path angle, the path angle indicating image for display; and re-planning a path of the intelligent lawn mower based on the set path angle and a preset algorithm. The present disclosure further provides a path planning system for the intelligent lawn mower.