Self-Propelled Robot Path Planning Across Multi-Height Obstacles
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Solution Overview
Problem
Conventional self-propelled robot path planning methods using two-dimensional maps are inefficient due to computational overhead and poor environment awareness, especially when dealing with obstacles at different heights, leading to irrational walking paths and low working efficiency.
Innovation Solution
A self-propelled robot path planning method that generates a multilayer environmental map by acquiring information of obstacles at different heights using sensor assemblies, processing this data to unite and intersect walkable regions, and planning a walking path based on synthetically processed information to reduce computational overhead and improve efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If three-dimensional maps are used to provide accurate environmental information for robots at different heights, then environment awareness is improved, but computational overhead increases and data processing time is prolonged
Solution Approach 1:
The patent segments the three-dimensional space into multiple two-dimensional detection layers at different heights. Each layer is processed independently to identify obstacles specific to that height level, avoiding the computational burden of processing the entire 3D space as a single unit while still capturing height-specific obstacle information.
Solution Approach 2:
The patent transforms the three-dimensional environmental mapping problem into a series of two-dimensional mapping problems by creating multiple 2D detection layers at different heights. This dimensionality reduction allows for more efficient processing while maintaining the essential 3D obstacle information needed for robot navigation.
2Productivity
If conventional two-dimensional maps are used for path planning, then computational overhead is reduced, but environment awareness is insufficient and walking paths become irrational
Solution Approach 1:
The patent segments the environmental mapping into multiple 2D layers, each representing a specific height level. This segmentation maintains computational efficiency of 2D processing while capturing the multi-height obstacle information that conventional single-layer 2D maps miss, enabling more rational path planning.
3Measurement precision
If sensor assemblies are arranged at different heights to detect obstacles, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the detection task across multiple height levels using sensor assemblies positioned at different heights. Each sensor detects obstacles in its specific detection layer, improving overall detection accuracy by capturing obstacles at various elevations without requiring a single complex omnidirectional sensor system.
Data Source
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AI summary
Provided are a self-propelled robot path planning method, a self-propelled robot and a storage medium. The method may include, a self-propelled robot walks in a to-be-operated space to acquire information of obstacles at different heights and generates a multilayer environmental map of the to-be-operated space. The method may also include information in the multilayer environmental map is synthetically processed to obtain synthetically processed data. Additionally, the method may include a walking path for the self-propelled robot is planned according to the synthetically processed data.