Mobile robot and control method
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Solution Overview
Problem
Conventional autonomous travel type cleaning devices face challenges in self-position estimation and movement path optimization, leading to inappropriate path selection and increased positional errors.
Innovation Solution
A mobile robot equipped with a range finding sensor, an acquisition unit, a first identification unit, a second identification unit, and a converter that identifies feature points and virtual points to adjust the movement path, ensuring effective self-position estimation and optimal path selection by converting the initial path to pass through virtual points within the range-finding range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the mobile robot follows the initial path acquired by the acquisition unit, then the movement path is simple and easy to follow, but the self-position estimation accuracy deteriorates when the path does not pass through detectable feature points
Solution Approach 1:
The system performs preliminary analysis of the initial path to identify feature points and determine whether the path passes through detectable regions. Before execution, the path is evaluated and converted if necessary, ensuring that the mobile robot follows an optimal path that enables accurate self-position estimation without real-time adjustments.
Solution Approach 2:
The converter acts as an intermediary between the acquisition unit and the drive unit. It receives the initial path, analyzes it against feature point locations, and generates a converted path that passes through detectable regions. This intermediary processing ensures that the path information transmitted to the drive unit is optimized for self-position estimation accuracy.
2Measurement precision
If the mobile robot moves along a path that passes through feature points, then self-position estimation accuracy is improved, but the movement path becomes longer and less efficient
Solution Approach 1:
Instead of requiring the path to pass through all feature points, the system identifies and passes through only the necessary feature points that provide sufficient self-position estimation accuracy. The converter determines the minimum set of feature points needed along the path, avoiding unnecessary detours while maintaining estimation precision.
Solution Approach 2:
The system adjusts path parameters dynamically by converting the initial path into a converted path that optimizes the balance between length and feature point coverage. The converter modifies path coordinates to pass through detectable regions while minimizing total path length, achieving efficient movement with adequate self-position estimation.
3Measurement precision
If the range finding sensor detects feature points frequently, then self-position estimation accuracy is improved, but the detection complexity and processing load increase
Solution Approach 1:
The system performs preliminary identification of feature points and their locations on the map before the mobile robot begins movement. The first identification unit pre-processes the environment map to locate feature points, and the converter pre-plans the path to pass through these identified points. This preliminary preparation reduces real-time detection complexity during actual movement.
Solution Approach 2:
The system extracts and focuses on only the necessary feature points that are relevant for self-position estimation along the planned path. Instead of processing all possible features in the environment, the identification units extract specific feature points that lie on or near the converted path, reducing the overall detection and processing load.
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
The solution enables the mobile robot to move along a more appropriate movement path, improving self-position estimation accuracy and reducing positional errors by detecting feature points and virtual points, thereby enhancing navigation efficiency.
Implementation Method 1
a range finding sensor having a predetermined range-finding range
Data Source
AI summary
A cleaning device includes: a range finding sensor; an acquisition unit which acquires a map and a first path along which the cleaning device is to move; a first identification unit which identifies a feature point which is a point where a distance between the object and the range finding sensor varies; a second identification unit which identifies a virtual point which is, among points on a virtual line segment, a point closest to the first path when the virtual line segment does not intersect with the first path, the virtual line segment extending toward the first path from the feature point, and having a maximum length within the predetermined range-finding range; a converter which converts the first path into a second path which passes through the virtual point; and a motor controller which causes the cleaning device to move along the second path.