Optical Obstacle Sensor Subsystem for Cliff and Wall Detection
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Solution Overview
Problem
Conventional proximity sensors for self-guiding devices, such as automatic vehicles and robots, face challenges in accurately detecting obstacles like cliffs and walls, particularly in determining distances and preventing collisions or falls without physical contact.
Innovation Solution
A sensor subsystem comprising a light emitter and a light sensor that projects and captures images of an indicator light, allowing for image analysis to determine spatial relationships and compute distances to obstacles, triggering avoidance measures when thresholds are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional proximity sensors (ultrasonic, infrared) are used to detect obstacles, then the device can detect the presence of nearby objects, but the measurement precision of distance is insufficient for accurate collision prevention
Solution Approach 1:
The patent transitions from conventional point-based or single-line sensor detection to a two-dimensional visual field analysis. By capturing images with a light sensor and analyzing the distribution of indicator light within the image, the system extracts distance information from spatial patterns rather than relying on traditional time-of-flight or intensity-based measurements, thereby improving measurement precision while maintaining detection reliability
Solution Approach 2:
The patent replaces conventional ultrasonic or infrared proximity sensors with an optical imaging system. Instead of using acoustic waves or simple infrared detection, the system projects visible indicator light and captures its reflection with a light sensor to create images, substituting mechanical/acoustic detection methods with optical imaging to achieve superior distance measurement precision
2Productivity
If the self-guiding machine travels at higher speed to improve productivity, then output increases, but the risk of collision with obstacles increases
Solution Approach 1:
The system continuously captures images and analyzes the visual field to detect obstacles at a distance before the machine reaches them. By identifying obstacles in advance through image analysis of the projected indicator light pattern, the machine can plan and execute avoidance maneuvers with sufficient time margin, enabling higher travel speeds while maintaining collision avoidance reliability
Solution Approach 2:
The system establishes a continuous feedback loop where the light sensor captures images, the controller analyzes the visual field to determine obstacle presence and distance, and the machine adjusts its trajectory accordingly. This real-time feedback mechanism allows the machine to travel at higher speeds while maintaining safety through continuous monitoring and immediate response to detected obstacles
3Measurement precision
If a complex sensor system is used to improve detection accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional sensor subsystem where the light emitter serves both as a illumination source for the machine's path and as a reference for distance measurement. The light sensor simultaneously captures images for obstacle detection and analyzes indicator light distribution for precise distance calculation. This multi-functionality reduces the need for separate dedicated sensors, achieving high measurement precision while controlling device complexity
Solution Approach 2:
The system uses its own emitted indicator light as the measurement reference, eliminating the need for external light sources or complex calibration equipment. The machine projects its own light, captures the reflection, and processes the image data internally, making the system self-sufficient and reducing overall complexity while maintaining high measurement precision
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
Effectively prevents collisions and falls by accurately determining distances and approaching obstacles, enabling timely avoidance maneuvers in self-guiding machines.
Implementation Method 1
The light emitter emits an indicator light being projected onto a path the self-guiding machine travels toward
Implementation Method 2
the light sensor captures one image at one time or a series of images containing the indicator light for a period of time
Data Source
AI summary
The disclosure is related to a method and a system for obstacle detection adapted to a self-guiding machine. The method is performed in the system including a controller for driving the system, a light emitter, a light sensor, an image processor and a central processor. The light emitter and the light sensor are set apart at a distance. When the light emitter emits an indicator light being projected onto a path the self-guiding machine travels toward, the light sensor senses the indicator light. An image containing the indicator light is generated. After analyzing the image, at least one feature of the indicator light being sensed can be obtained and used to obtain a spatial relationship between the self-guiding machine and an obstacle. The spatial relationship allows the system to determine if the self-guiding machine will collide with a wall or fall from a cliff.