Robotic Lawn Mower Path Planning for Efficient Obstacle Traversal
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Solution Overview
Problem
Existing robotic lawn mowers inefficiently traverse obstacles, leading to increased mowing time and power consumption due to unnecessary paths taken during edge mowing.
Innovation Solution
An obstacle traversal method and apparatus that determines obstacle positions, selects target points, and generates optimal mowing paths to efficiently traverse obstacles, reducing power consumption and improving operation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the robotic lawn mower performs mowing along edges of obstacles in sequential order, then complete mowing coverage is achieved, but unnecessary paths are taken increasing total mowing time and power consumption
Solution Approach 1:
The system performs preliminary actions by pre-calculating and planning the complete mowing path in advance, including all edge mowing sequences, before the actual mowing operation begins. This allows the robot to traverse obstacles efficiently without making suboptimal sequential decisions during execution.
Solution Approach 2:
The path planning system dynamically adjusts the mowing sequence and paths based on obstacle positions, robot starting location, and boundary conditions. The system can recalculate optimal paths during operation when new obstacles are detected or when recharging interruptions occur, adapting to changing conditions to minimize total travel distance.
2Manufacturing precision
If the robotic lawn mower performs mowing along edges of obstacles in sequential order, then complete mowing coverage is achieved, but power consumption increases due to unnecessary paths
Solution Approach 1:
The system performs preliminary actions by pre-calculating and planning the complete mowing path in advance, including all edge mowing sequences, before the actual mowing operation begins. This allows the robot to traverse obstacles efficiently without making suboptimal sequential decisions during execution.
Solution Approach 2:
The path planning system dynamically adjusts the mowing sequence and paths based on obstacle positions, robot starting location, and boundary conditions. The system can recalculate optimal paths during operation when new obstacles are detected or when recharging interruptions occur, adapting to changing conditions to minimize total travel distance.
3Use of energy by moving object
If the robotic lawn mower takes direct paths between obstacles, then power consumption is reduced, but mowing coverage along obstacle edges may be incomplete
Solution Approach 1:
The mowing task is segmented into distinct phases: traversing between obstacles and performing edge mowing along obstacles. The system plans efficient traversal paths between obstacles while separately planning complete edge mowing sequences for each obstacle, ensuring both energy efficiency and coverage completeness.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and planning the complete mowing path in advance, including all edge mowing sequences, before the actual mowing operation begins. This allows the robot to traverse obstacles efficiently without making suboptimal sequential decisions during execution.
Data Source
AI summary
An obstacle traversal method and apparatus, a robotic lawn mower, and a storage medium are provided. The method includes: determining position information corresponding to at least one obstacle in a current scene; determining a target point corresponding to each of the at least one obstacle based on the position information; and generating a mowing path based on the target point corresponding to each of the at least one obstacle, and controlling the robotic lawn mower to traverse the at least one obstacle based on the mowing path.


