Mobile robot and control method therefor
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Solution Overview
Problem
Conventional mobile robots face challenges in accurately detecting obstacles, particularly cliffs, due to limitations in distance measurement methods and difficulty in recognizing three-dimensional shapes, leading to errors in navigation and potential falls.
Innovation Solution
A mobile robot equipped with a first pattern emission unit emitting light toward the lower side and a second pattern emission unit emitting light toward the upper side, combined with an image acquirer to capture and analyze the patterns, allowing for rapid detection and avoidance of cliffs by determining the shape of the obstacle and controlling the robot's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single light source emits light at a predetermined angle, then the device complexity is reduced, but the obstacle detection range and three-dimensional shape recognition capability are limited
Solution Approach 1:
The single light source is divided into multiple light sources (first light source and second light source) positioned at different locations. Each light source emits light at different angles to illuminate different portions of the obstacle, thereby expanding the overall detection range and enabling three-dimensional shape recognition while maintaining relatively simple device structure
Solution Approach 2:
The patent transitions from a single-angle illumination approach to multi-angle illumination by positioning light sources at different spatial locations. This dimensional expansion allows the system to capture obstacle information from multiple perspectives, enabling three-dimensional shape recognition and significantly expanding the effective detection range
2Device complexity
If infrared rays or ultrasonic waves are used for distance measurement, then the measurement method is simple, but a large amount of light or sound is scattered by obstacles causing significant measurement errors
Solution Approach 1:
The patent replaces infrared or ultrasonic measurement methods with a visual pattern recognition system using visible light and camera. This substitution eliminates scattering issues associated with infrared and ultrasonic waves, as visible light patterns can be clearly captured and analyzed by the image processing unit, significantly improving measurement precision while maintaining system simplicity
Solution Approach 2:
The patent uses visible light patterns with distinct visual characteristics that can be easily differentiated by the camera and image processing unit. The pattern recognition approach leverages the visual system's ability to detect color and shape variations, providing accurate distance and obstacle information without the scattering problems that plague infrared and ultrasonic methods
3Reliability
If the mobile robot repeatedly approaches the cliff to check for cliffs, then the detection reliability is improved, but the time required to avoid the cliff increases significantly
Solution Approach 1:
The patent performs preliminary cliff detection by capturing an image of the area in front of the robot before making any movement decisions. The image processing unit analyzes this preliminary image to identify cliffs and other obstacles, allowing the robot to plan its path in advance and avoid cliffs in a single pass rather than requiring repeated approach-and-check cycles
Solution Approach 2:
The patent creates a visual copy (image) of the environment in front of the robot and analyzes this copy to detect cliffs. This copying approach allows comprehensive analysis of the entire visible area simultaneously, providing reliable cliff detection information without requiring the robot to physically approach the cliff multiple times, thereby significantly reducing the time required for safe navigation
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 more accurate obstacle detection, rapid determination of cliffs, and effective avoidance of obstacles, preventing the robot from falling off stairs or other elevated surfaces.
Implementation Method 1
a first pattern emission unit disposed on a front surface of the body and for emitting first pattern light toward a lower side of a front side of the body, a second pattern emission unit disposed on the front surface of the body, disposed below the first pattern emission unit, and for emitting second pattern light toward an upper side of the front side of the body
Implementation Method 2
an image acquirer disposed on the front surface of the body and for acquiring an image of the front side of the body
Data Source
Figure 1a
Figure 1b
Figure 2
AI summary
A mobile includes a first pattern emission unit for emitting first pattern light toward a floor in a cleaning area in front of a body and a second pattern emission unit for emitting second pattern light upward in front of the body, acquires an image obtained by emitting light of each of the patterns emitted from the first pattern emission unit and the second pattern unit through an image acquirer, detects a pattern from the acquired image to determine an obstacle, detects a cliff depending on a shape or position of the pattern, and is driven along a path along which the mobile robot does not fall off the cliff to avoid the cliff, and thus, preferentially determines whether a cliff is present, differentiates between a threshold and a cliff such as a stair to be driven or avoid the obstacle, is effectively driven due to the rapid determination and operation of the mobile obstacle, and prevents the mobile robot from falling off the cliff such as a stair.