Robotic Garden Tool Obstacle Mapping for Virtual Boundary Navigation
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Solution Overview
Problem
Existing robotic garden tools face challenges in efficiently creating accurate virtual boundaries within operating areas, particularly in complex environments with obstacles, which affects their navigation and operation efficiency.
Innovation Solution
A robotic garden tool system that includes sensors, such as millimeter wave radar and optical cameras, and an electronic processor to detect obstacles, generate mapping information, and control movement to create virtual boundaries around obstacles, allowing the tool to navigate and operate efficiently while avoiding obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robotic garden tool uses sensors to detect obstacles and create virtual boundaries, then the navigation accuracy and operational efficiency are improved, but the device complexity increases
Solution Approach 1:
The system segments the operating area into zones based on obstacle detection, creating virtual boundaries that divide the workspace. This allows the robotic tool to navigate more efficiently by treating different areas differently, improving measurement precision while managing complexity through spatial segmentation.
Solution Approach 2:
The electronic processor acts as an intermediary between the sensors and the wheel motors, processing sensor data to create virtual boundaries and translating this information into navigation commands. This intermediary layer manages the complexity by centralizing the decision-making logic.
2Productivity
If the robotic garden tool maps obstacles and creates virtual boundaries, then the path planning efficiency is improved, but the time required for initial mapping increases
Solution Approach 1:
The system performs preliminary mapping actions by detecting obstacles and creating virtual boundaries before actual mowing operations begin. This preliminary action establishes the navigation framework in advance, improving subsequent path planning efficiency while accepting the initial time investment.
Solution Approach 2:
The robotic garden tool performs self-mapping by autonomously detecting obstacles and creating its own virtual boundaries without external intervention. This self-service capability allows the system to build its navigation model independently, improving efficiency while the mapping time is absorbed into the initial setup phase.
3Reliability
If the robotic garden tool uses multiple sensors for obstacle detection, then the reliability of obstacle identification is improved, but the cost and complexity of the system increases
Solution Approach 1:
The system merges data from multiple sensor types (millimeter wave radar and optical cameras) to create a comprehensive obstacle detection capability. By combining the strengths of different sensors, the system improves reliability while managing complexity through integrated processing in the electronic processor.
Solution Approach 2:
The sensor system is designed to detect multiple types of obstacles (trees, rocks, buildings, water bodies) using the same sensor array. This multi-functionality improves reliability across different obstacle types while avoiding the need for specialized sensors for each obstacle category.
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
Enables the robotic garden tool to accurately map and navigate around obstacles, improving its operational efficiency and path planning within the operating area, allowing for more precise and efficient mowing or maintenance tasks.
Implementation Method 1
the at least one sensor may include at least one selected from the group consisting of a millimeter wave radar sensor, an optical camera, an infrared sensor, or combinations thereof
Implementation Method 2
the at least one sensor may include at least one selected from the group consisting of a millimeter wave radar sensor, an optical camera, an infrared sensor, or combinations thereof
Implementation Method 3
the at least one sensor may include at least one selected from the group consisting of a millimeter wave radar sensor, an optical camera, an infrared sensor, or combinations thereof
Data Source
AI summary
A robotic garden tool includes at least one sensor configured to generate signals associated with an object within an operating area. A first electronic processor of the robotic garden tool receives, from the at least one sensor, an obstacle signal associated with an obstacle located within the operating area. The first electronic processor determines a first location of the robotic garden tool at a time corresponding to when the first electronic processor received the obstacle signal. The first electronic processor determines a second location of the obstacle based on the obstacle signal and the first location of the garden tool. The first electronic processor generates mapping information of the operating area that includes a virtual boundary based on the second location of the obstacle. The first electronic processor controls the robotic garden tool in the operating area to remain outside of the virtual boundary based on the mapping information.