Autonomous Work Area Sensing With Virtual Boundary Mapping
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Solution Overview
Problem
Current autonomous lawn mowers and similar devices face challenges in accurately and efficiently defining and navigating within complex work areas, particularly in environments with obstacles and dynamic boundaries, without human intervention.
Innovation Solution
The method involves using a detection unit to autonomously detect the environment and a marking object to define the work area, with the marking object being detected electromagnetically or optically, allowing the autonomous device to create a virtual map and navigate while maintaining a safe distance from obstacles, enabling flexible and reliable area definition and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If boundary wire is installed to delineate working area, then working area definition is achieved, but device complexity and installation effort increase
Solution Approach 1:
The patent extracts the boundary wire from the system by replacing it with a camera-based detection system. The physical wire that previously defined the working area is removed, and its function is transferred to the camera unit that captures images to determine the working area boundaries automatically.
Solution Approach 2:
The patent replaces the mechanical boundary wire system with an optical detection system. Instead of using physical wires to delineate the working area, the system uses a camera to capture images and process them to determine the working area, substituting mechanical/physical methods with optical and computational methods.
2Reliability
If manual pushing or remote control learning is used to detect work area, then working area is captured, but time consumption and operational complexity increase
Solution Approach 1:
The autonomous work device performs self-learning by autonomously moving within the environment and capturing images with its camera unit. The device independently processes these images to generate a map and determine the working area without requiring manual pushing or remote control operation, making the system self-sufficient in the learning process.
Solution Approach 2:
The system performs preliminary autonomous movement and image capture to establish the working area boundaries before actual work begins. By pre-mapping the environment and identifying the working area in advance through autonomous exploration, the system prepares the operational parameters beforehand, eliminating the need for time-consuming manual learning procedures.
3Ease of operation
If autonomous navigation without boundary wire is implemented, then ease of operation improves, but reliability of work area definition decreases
Solution Approach 1:
The patent replaces the mechanical boundary wire system with an optical image processing system. The camera unit captures images of the environment, and image processing algorithms analyze these images to accurately determine the working area boundaries, substituting physical wire-based definition with computational vision-based definition.
Solution Approach 2:
The system creates a virtual copy or map of the physical environment by capturing images and processing them to generate a digital representation of the working area. This virtual map serves as a copy of the physical space, allowing the autonomous device to navigate and define boundaries without physical wires while maintaining accuracy through image analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient, accurate, and safe navigation of autonomous devices within complex environments by enabling precise definition of work areas, quick detection of hazards, and flexible area changes, enhancing the reliability and efficiency of autonomous operations.
Implementation Method 1
The marking object is detected electromagnetically or optically
Implementation Method 2
The marking object is detected electromagnetically or optically
Data Source
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AI summary
The invention relates to methods for sensing at least one working region (10a; 10b; 10c) of an autonomous working device (30a; 30b; 30c), in particular an autonomous lawn mower, in particular by means of at least one first sensing unit (32a; 32b; 32c) and by means of at least one second sensing unit (34a; 34b; 34c). According to the invention, an environment (12a; 12b; 12c) is sensed, in particular by means of the first sensing unit (32a; 32b; 32c), in at least one first step and the working region (10a; 10b; 10c) is defined within the environment (12a; 12b; 12c), in particular by means of the second sensing unit (34a; 34b; 34c), in at least one second step.