Cleaning Robot Transparent Obstacle Detection With 2D Depth Sensing
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Solution Overview
Problem
Conventional cleaning robots can only detect one-dimensional depth information and often bump into obstacles due to dead zones between different sensors, leading to noise generation and damage to furniture and the robot itself.
Innovation Solution
A cleaning robot equipped with a diffractive optical element, light sources, and an image sensor that projects line and speckle patterns to calculate two-dimensional depth information, allowing the robot to detect obstacles and maintain a fixed distance from walls using a single image sensor, eliminating the need for multiple sensors and reducing dead zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple different sensors are used to detect front distance and wall distance, then detection coverage is improved, but dead zones between sensors cause frequent bumping into obstacles
Solution Approach 1:
The patent merges multiple sensor functions into a single image sensor that captures both front distance and wall distance information simultaneously. The image sensor projects line patterns and analyzes reflected light to obtain two-dimensional depth information, eliminating dead zones between separate sensors and preventing frequent bumping into obstacles.
Solution Approach 2:
The patent transitions from one-dimensional depth detection to two-dimensional depth information by using an image sensor to capture spatial relationships in both front and side directions. This dimensional expansion allows simultaneous detection of obstacles at various distances and angles without requiring multiple separate sensors.
2Device complexity
If conventional one-dimensional depth sensors are used, then device complexity is reduced, but the robot cannot identify obstacle appearance or calculate wall distance
Solution Approach 1:
The image sensor performs multiple functions simultaneously: detecting front obstacles, calculating wall distance, identifying obstacle appearance, and providing two-dimensional depth information. This multi-functional approach replaces multiple specialized sensors while enhancing measurement capabilities.
Solution Approach 2:
The patent changes the detection parameter from one-dimensional distance to two-dimensional depth information by analyzing the spatial distribution of reflected light patterns. The image sensor captures not only distance but also angular information, enabling comprehensive obstacle detection and wall distance calculation.
3Measurement precision
If multiple sensors are deployed for obstacle detection, then detection accuracy is improved, but the robot structure becomes more complex and service life is reduced
Solution Approach 1:
The patent combines multiple detection functions into a single image sensor system, reducing the number of components that can fail. By eliminating dead zones between sensors, the system prevents bumping incidents that cause mechanical damage to furniture and the robot, thereby extending service life.
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 robot effectively detects two-dimensional depth information and maintains a consistent distance from walls, reducing collisions and extending its service life by utilizing a single image sensor to capture and process pattern images, thereby improving navigation and cleaning efficiency.
Implementation Method 1
a first light source, a first diffractive optical element... The first light source is configured to emit light through the first diffractive optical element to project a line pattern on an obstacle
Implementation Method 2
The image sensor is configured to acquire an image with a field of view toward the moving direction
Data Source
AI summary
There is provided a cleaning robot including a light source module, an image sensor and a processor. The light source module projects a line pattern and a speckle pattern toward a moving direction. The image sensor captures an image of the line pattern and an image of the speckle pattern. The processor calculates one-dimensional depth information according to the image of the line pattern and calculates two-dimensional depth information according to the image of the speckle pattern.