Robotic Lawn Mower Closed-Route Planning for Obstacle Avoidance
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Solution Overview
Problem
Existing robotic lawn mowers often travel long distances due to improper planning of preset routes, leading to reduced mowing efficiency and increased power consumption.
Innovation Solution
An intelligent obstacle avoidance method that generates an adaptive obstacle avoidance path based on detected obstacles, optimizing the mowing route to be closed, where the starting and ending points are the same, thereby reducing unnecessary travel and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a preset route is used for the robotic lawn mower, then the mowing operation can be controlled, but the actual route traveled becomes very long, reducing mowing efficiency and consuming more stored power
Solution Approach 1:
The patent transitions from a static preset route to a dynamic adaptive route planning system. The robotic lawn mower uses real-time sensor data to detect obstacles and dynamically adjusts the mowing path during operation. This allows the system to maintain operational control while optimizing the actual travel distance based on current environmental conditions, thereby improving mowing efficiency without sacrificing ease of operation.
Solution Approach 2:
The patent implements a feedback mechanism where the robotic lawn mower continuously monitors its environment using sensors, compares the actual situation with the planned route, and adjusts the path accordingly. The system receives feedback about obstacles and terrain conditions, processes this information, and modifies the mowing route in real-time. This closed-loop control enables the mower to avoid unnecessary travel while maintaining systematic coverage of the lawn area.
2Ease of operation
If a preset route is used for the robotic lawn mower, then the mowing operation can be controlled, but the stored power is consumed more rapidly
Solution Approach 1:
The system dynamically adjusts the mowing route based on real-time obstacle detection and environmental conditions. By adapting the path to actual conditions rather than following a rigid preset route, the robotic lawn mower minimizes unnecessary travel distance and energy expenditure. The dynamic route optimization ensures that power is consumed only for essential movement, reducing overall stored power consumption while maintaining operational control.
Solution Approach 2:
The feedback mechanism enables the robotic lawn mower to monitor power consumption levels and environmental conditions simultaneously. When obstacles or terrain conditions suggest that the preset route would require excessive energy expenditure, the system receives feedback and adjusts the route to optimize energy efficiency. This real-time adaptation reduces stored power consumption by eliminating redundant travel while preserving the ease of controlled operation.
3Reliability
If the robotic lawn mower follows a long actual route, then all working regions can be covered, but the mowing efficiency is reduced
Solution Approach 1:
The patent employs dynamic route planning that adapts to real-time conditions while ensuring complete coverage of working regions. The system uses sensor data to identify necessary travel paths and eliminates redundant segments. By dynamically optimizing the route based on actual obstacle locations and terrain features, the robotic lawn mower maintains reliable coverage of all required areas while significantly reducing the total travel distance, thereby improving mowing efficiency without compromising coverage completeness.
Solution Approach 2:
The feedback system continuously monitors whether all working regions are being covered and adjusts the route accordingly. Rather than following a fixed preset route that may include unnecessary segments, the system receives feedback about coverage status and environmental conditions, then optimizes the path to achieve complete coverage with minimal travel. This ensures that reliability of coverage is maintained while productivity through reduced travel time is improved.
Data Source
AI summary
According to a mowing method disclosed in embodiments of the present disclosure, a plurality of preset working regions are obtained in response to a mowing trigger request for a robotic lawn mower; a mowing sequence corresponding to the working regions is output based on region information of the working regions; a closed mowing route covering all the working regions is generated based on the mowing sequence, current position information of the robotic lawn mower, and a mowing direction, where a starting point and an ending point of the closed mowing route are the same; and the robotic lawn mower is controlled to perform a mowing operation based on the closed mowing route.