Mobile Robot Vision Using Resized ROI and Dual-Bandpass Filtering
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Solution Overview
Problem
Conventional cleaning robots require multiple sensors for obstacle detection, positioning, and object recognition, leading to increased complexity and power consumption.
Innovation Solution
A mobile robot utilizing a single optical sensor with different light sources (laser diode and light emitting diode) to capture image frames for obstacle avoidance, visual simultaneous localization and mapping, and object recognition, reducing computation and power consumption by determining a region of interest and using a dual-bandpass filter for differential image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sensors are used for obstacle detection, positioning, and object recognition, then the robot's detecting functions are improved, but the device complexity and power consumption increase
Solution Approach 1:
The patent applies a single optical sensor to perform multiple detecting functions including obstacle detection, positioning, and object recognition by capturing different types of image frames (first image frame for obstacle detection, second image frame for positioning, third image frame for object recognition) under different lighting conditions, thereby eliminating the need for multiple separate sensors and reducing device complexity while maintaining versatile detecting capabilities
2Measurement precision
If the size of the ROI is extended to integer times of predetermined size, then the recognition correctness is improved, but the computation loading increases
Solution Approach 1:
The patent extends the region of interest (ROI) to integer times of predetermined size when the original ROI size is not an integer multiple, incorporating adjacent pixel rows or columns to achieve the extended size. This partial extension approach ensures sufficient recognition correctness by maintaining the integer multiple relationship while avoiding unnecessary computation on excessively large regions, thus balancing recognition accuracy with computational efficiency
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 efficient obstacle detection, accurate positioning, and object recognition with reduced computational and power demands, enhancing the robot's functionality while optimizing resource usage.
Implementation Method 1
The mobile robot includes a linear light source, an optical sensor, a dual-bandpass filter and a processor. The dual-bandpass filter is arranged at a light incident path of the optical sensor.
Data Source
AI summary
There is provided a mobile robot that performs the obstacle avoidance, positioning and object recognition according to image frames captured by the same optical sensor. The mobile robot includes an optical sensor, a light emitting diode, a laser diode and a processor. The processor identifies an obstacle and a distance thereof according to image frames captured by the optical sensor when the laser diode is emitting light. The processor further performs the positioning and object recognition according to image frames captured by the optical sensor when the light emitting diode is emitting light.