Mobile Robot Heading Guidance via Light Pattern Symmetry
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Solution Overview
Problem
Current methods for determining a mobile robot's orientation in an environment, such as SLAM, are costly and require excessive processing power, necessitating a simpler and more cost-effective solution for automatically guiding the robot's heading relative to environmental surfaces.
Innovation Solution
A method utilizing a camera and collimated light emitters to project a light pattern onto surfaces, with image analysis by a processor to detect distortion and adjust the robot's heading, potentially aided by machine learning algorithms to achieve desired orientations efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM is used to identify the location and orientation of a robot, then the robot can determine its orientation in the environment, but the cost of the robot increases and more processing power and time are required
Solution Approach 1:
The patent extracts the orientation determination function from complex SLAM systems and implements it through a simplified dedicated subsystem using light emitters and camera arrays. This separate, specialized system achieves orientation detection without requiring full SLAM processing power or additional expensive components.
Solution Approach 2:
The patent uses light emitters to project patterns onto surfaces and cameras to capture distorted images of these patterns. By analyzing the distortion of copied light patterns, the system determines orientation without needing direct environmental mapping or complex sensor fusion required by SLAM.
2Measurement precision
If SLAM is used to determine robot orientation, then accurate location and orientation identification is achieved, but excessive processing power and time are consumed
Solution Approach 1:
The patent employs inexpensive light emitters and standard cameras instead of expensive specialized sensors. The light patterns are temporary projections that are quickly captured and analyzed, requiring minimal processing time and energy compared to continuous SLAM operations.
Solution Approach 2:
The system performs only the specific function of orientation detection through light pattern analysis, rather than executing complete environmental mapping and localization. This partial action achieves the needed orientation information with significantly reduced processing requirements.
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
Enables cost-effective automatic heading adjustment of mobile robots relative to surfaces, improving orientation determination without the need for expensive components or excessive processing power, and enhances accuracy through machine learning.
Implementation Method 1
One or more collimated light emitters positioned on a mobile robotic device emit collimated light beams in a predetermined pattern
Implementation Method 2
The processor analyzes the images to determine whether the image of the light pattern is distorted. Distortion of the image will occur if the plane upon which the image is projected is not parallel to the plane in which the light is emitted
Data Source
AI summary
The present invention introduces a method for guiding or directing the heading of a mobile robotic device. A light pattern is projected from a light emitting unit disposed on a robotic device. The angle of the plane of the projection of the light pattern with respect to a heading of the robotic device is preset, but may be any angle as desired by a manufacturer or operator. A camera positioned in a plane parallel to the plane of the light pattern projection captures images of the projected light pattern on surfaces substantially opposite the light emitting unit. Images are processed to check for reflection symmetry about a vertical centerline of the images. Upon detecting an image that does not have reflection symmetry, the robotic device turns to adjust its heading with relation to the surfaces in the environment on which the light pattern is projected. Turning amounts and directions are provided to the controller and may be based on analysis of the last image captured.