Mobile Robot Path Planning Using Safety Range Skeleton Maps
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Solution Overview
Problem
Current path planning algorithms for mobile robots are inflexible and do not adequately consider the geometry of the robot, leading to potential collisions and increased complexity in map modeling, especially in large environments.
Innovation Solution
A path planning method based on image processing that preprocesses map images by calculating a safety distance and marking a safety range, using skeleton feature extraction and Dijkstra's algorithm to generate an optimal path, while segmenting and optimizing paths to ensure safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional map formats (grid map, directed map, undirected map) are used for path planning, then the path planning algorithm can be implemented, but the map modeling process becomes extremely complex and requires extensive human input, especially in large environments
Solution Approach 1:
The patent replaces manual map modeling with automatic image processing. The mobile robot captures environment images using its camera, and the system automatically processes these images to generate the path planning map, eliminating the need for manual grid map creation and reducing map modeling complexity significantly
Solution Approach 2:
The mobile robot performs self-mapping by capturing images of its environment and automatically processing them to create the path planning map. This self-service approach eliminates the need for external human input in map building, making the process autonomous and scalable to large environments
2Device complexity
If the mobile robot is treated as a mass point in path planning algorithms, then the algorithm complexity is reduced, but the robot geometry is not considered, resulting in collision risk during movement
Solution Approach 1:
The patent performs preliminary action by pre-calculating the safety distance based on the robot's geometric features before path planning. The safety range is marked on the map image in advance, and the path planning algorithm operates on this pre-processed map, ensuring collision avoidance without increasing algorithm complexity
Solution Approach 2:
The patent applies local quality by considering the robot's specific geometric features (length, width, turning radius) to calculate a specific safety distance. This localized approach accounts for the robot's actual dimensions in the path planning process, ensuring reliable collision avoidance while maintaining algorithm efficiency
3Device complexity
If the safety distance is not considered in path planning, then the path planning is simpler, but the mobile robot may collide with obstacles during movement
Solution Approach 1:
The patent performs preliminary action by calculating the safety distance based on robot geometric features and marking the safety range on the map image before path planning. This pre-processing step ensures that the path planning algorithm operates on a map that already accounts for safety margins, maintaining simplicity while ensuring movement safety
Data Source
AI summary
A path planning method of mobile robots based on image processing is provided and includes: S1, preprocessing a map image: calculating a safety distance between a mobile robot and a surrounding obstacle during a movement of the mobile robot based on external geometric features of the mobile robot, forming a circular range on the map image with a expansion point as a center and the safety distance as an expansion radius to set a safety range, and marking the safety range; performing skeleton feature extraction on the map image after the marking to obtain a reference path map; S2, obtaining an initial path; and S3, optimizing the initial path. The path planning method improves the flexibility of the algorithm and has high robustness and operational efficiency, and the optimal path obtained can ensure the moving safety of the mobile robot.