Mobile Robot Visual Sensing for Real-Time Obstacle Mapping
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Solution Overview
Problem
Conventional mobile robots face inaccuracies in obstacle detection and floor condition recognition, particularly with ultrasonic and infrared sensors, leading to errors in distance measurement and inability to handle sudden path changes.
Innovation Solution
The mobile robot employs an optical pattern sensor with a laser diode and structured light camera to emit and analyze a cross-shaped optical pattern, allowing precise distance measurement and obstacle recognition, enabling accurate path planning and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ultrasonic or infrared sensors are used for obstacle detection, then the robot can detect obstacles to some degree, but the measurement precision of distance and floor conditions deteriorates
Solution Approach 1:
The patent replaces ultrasonic and infrared sensors with a camera-based visual sensing system. The camera captures images of the environment, and through image processing algorithms, the robot determines obstacle locations, distances, and floor conditions. This substitution of mechanical/acoustic sensing with optical-electronic sensing resolves the contradiction by achieving both reliable obstacle detection and precise measurement without the inherent limitations of ultrasonic/infrared methods.
2Ease of operation
If the robot generates a map and travels based on the map, then navigation is enabled, but the robot cannot cope with sudden path changes or store data of paths already passed
Solution Approach 1:
The patent implements continuous real-time image acquisition and processing during robot movement. The camera constantly captures new environmental data, and the system processes these images to detect obstacles and update the navigation path dynamically. This feedback mechanism allows the robot to respond to sudden path changes by continuously adapting its route based on current visual information rather than relying solely on pre-generated maps, thereby improving adaptability while maintaining autonomous 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
This solution enhances the accuracy of obstacle detection and floor condition recognition, allowing the mobile robot to effectively navigate and adapt to changing environments by generating a local area map and updating it in real-time, improving cleaning efficiency and path management.
Implementation Method 1
an optical pattern sensor with a laser diode and structured light camera to emit and analyze a cross-shaped optical pattern
Data Source
AI summary
Data within a designated distance from a main body of the mobile robot is accumulated and stored to form a local area map. A traveling direction or a rotating direction is set while avoiding an obstacle around the main body and a path may be readily set. Repetition of unnecessary operation is prevented and thus a traveling velocity based on rapid movement may be improved. Obstacles are readily avoided and cleaning efficiency may be improved.