Robot Path Planning With Bow-Shaped Coverage and Raster Mapping
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Solution Overview
Problem
Current path planning methods for household sweeping robots face challenges in building accurate environmental maps, navigating around obstacles, and ensuring complete room coverage, particularly in planning traversal strategies.
Innovation Solution
A low-cost path planning method that divides the operating space into rectangular virtual regions, using sensors for distance, angle, collision, and obstacle information to create a raster map, allowing the robot to traverse in a bow-shaped pattern, marking pass points, obstacle points, and collision points, and analyzing the map in real-time to determine full coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If planning traversal is used to achieve efficient room coverage, then productivity is improved, but device complexity increases due to need for environmental mapping and real-time path planning
Solution Approach 1:
The operating space is divided into multiple rectangular virtual regions, simplifying the path planning problem by breaking it down into manageable segments. The robot systematically traverses each region using a standardized bow-shaped pattern, reducing the complexity of real-time decision-making while maintaining high cleaning efficiency.
2Measurement precision
If environmental mapping is implemented for accurate navigation, then measurement precision is improved, but loss of time increases due to map building and processing
Solution Approach 1:
Virtual regions are pre-defined with standardized dimensions and layouts before the robot begins cleaning. This preliminary structuring of space eliminates the need for complex real-time environmental mapping, as the robot simply needs to identify which pre-defined region it is in and follow the corresponding bow-shaped traversal pattern.
3Device complexity
If random traversal is used to reduce system complexity, then device complexity is reduced, but productivity decreases due to lower cleaning efficiency
Solution Approach 1:
The robot employs a dynamic bow-shaped traversal pattern that adapts to each virtual region's boundaries and obstacles. Within each region, the robot dynamically adjusts its path while maintaining the bow-shaped structure, combining the simplicity of predefined patterns with the efficiency of adaptive navigation to achieve both low device complexity and high productivity.
Data Source
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AI summary
A path planning method of an intelligent robot includes: dividing an operating space into a plurality of rectangular virtual regions, and an area of each rectangular virtual region of the plurality of rectangular virtual regions is n*m square meters; controlling the intelligent robot to traverse the each rectangular virtual region with a bow-shaped behaviour; when traversing with the bow-shaped behaviour, building, by the intelligent robot, a raster map with distance information acquired by the distance information sensor, angle information acquired by the angle information sensor, collision information acquired by the collision detection sensor and obstacle information acquired by the obstacle detection sensor, and marking, by the intelligent robot, pass points, obstacle points and collision points; analyzing the raster map in real time to determine whether the entire operating space has been fully traversed, and when the entire operating space has been fully traversed, entering into the next step and when the entire operating space has not been fully traversed, returning to the step of controlling the intelligent robot to traverse the each rectangular virtual region with the bow-shaped behaviour; controlling the intelligent robot to make an alongst behaviour, and marking alongst behaviour points on the raster map.