Mobile Robot Heading Guidance Using Visual Feature Mapping
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Solution Overview
Problem
Mobile robots lack an efficient method to automatically maintain a desired heading relative to their environment, such as walls, which is crucial for tasks like navigation and mapping.
Innovation Solution
A robotic device equipped with a camera, sensors, and a processor that captures images and sensor data to generate a map of the environment, identifies features, and adjusts its heading by emitting collimated light beams and analyzing distortions in the projected light pattern to maintain the desired orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a mobile robot uses traditional sensor-based navigation methods, then it can perform basic movement and mapping tasks, but it cannot automatically maintain a desired heading relative to environmental features like walls
Solution Approach 1:
The patent introduces light emitters as an intermediary component that projects visible light patterns onto environmental surfaces. The camera captures these projected patterns, and the processor analyzes the distortion of the light patterns to determine heading orientation. This intermediary light-based system bridges the gap between traditional sensor navigation and the new vision-based heading maintenance capability, allowing the robot to automatically maintain desired headings relative to walls and other environmental features without requiring complex mechanical or sensor-based orientation systems
2Measurement precision
If the robot uses camera-based vision systems to identify environmental features, then it can maintain heading relative to walls, but the system becomes more complex and requires additional processing power
Solution Approach 1:
The patent transforms the camera's function from capturing general environmental images to specifically capturing projected light patterns with known geometric parameters. By projecting light patterns with predetermined characteristics and analyzing their distortion parameters, the system achieves precise heading measurements. The processor compares the captured light pattern parameters against expected parameters to calculate heading orientation, converting complex visual scene analysis into a more manageable parameter-matching problem that improves measurement precision while controlling processing complexity
3Reliability
If the robot relies on sensor data alone for navigation, then it can map the environment, but it accumulates error over time and cannot maintain consistent heading orientation
Solution Approach 1:
The patent implements a feedback mechanism where the camera continuously captures light pattern projections onto environmental surfaces, and the processor analyzes the distortion of these patterns to determine the robot's heading orientation. This visual feedback loop provides continuous, absolute heading references based on environmental features rather than integrated sensor data. The system compares the captured light pattern orientation against the desired heading and generates correction signals to maintain consistent orientation, eliminating the drift and error accumulation inherent in sensor-only navigation systems
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 the robotic device to autonomously maintain a consistent heading relative to environmental features, improving navigation and mapping accuracy by using machine learning algorithms to refine heading adjustments and compensate for noise and bias in sensor measurements.
Implementation Method 1
capturing, with the camera, one or more images of an environment of the robotic device
Implementation Method 2
capturing, with the plurality of sensors, sensor data of the environment
Implementation Method 3
determining, with the processor, a position and orientation of the robotic device relative to the feature based on at least one of the one or more images and the sensor data
Data Source
AI summary
A robotic device, including a tangible, non-transitory, machine readable medium storing instructions that when executed by a processor effectuates operations including: capturing, with the camera, one or more images of an environment of the robotic device; capturing, with the plurality of sensors, sensor data of the environment; generating or updating, with the processor, a map of the environment; identifying, with the processor, one or more rooms in the map; receiving, with the processor, one or more multidimensional arrays including at least one parameter that is used to identify a feature included in the one or more images; determining, with the processor, a position and orientation of the robotic device relative to the feature; and transmitting, with the processor, a signal to the processor of the controller to adjust a heading of the robotic device.