Autonomous Mobile Device Reflective Surface Detection
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Solution Overview
Problem
Autonomous mobile devices (AMDs) face challenges in accurately mapping physical spaces due to reflective surfaces like glass and mirrors, which can cause incorrect data collection and collision hazards, and may fail to detect transparent surfaces adequately.
Innovation Solution
The AMD employs a method involving LEDs to emit light, cameras to capture images, and algorithms to identify candidate reflections, confirming their presence by turning off the light and using stereovision or ultrasound to determine distance and orientation of reflective surfaces, allowing for accurate mapping and collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional mapping methods are used, then mapping speed is maintained, but measurement precision deteriorates due to reflective surfaces causing incorrect data collection
Solution Approach 1:
The system dynamically switches between active illumination mode (LEDs on) and detection mode (LEDs off) to differentiate reflective surfaces from transparent surfaces. This temporal dynamic approach allows the same sensor to serve multiple detection purposes without requiring separate dedicated sensors for each surface type.
Solution Approach 2:
The LEDs are activated periodically in a controlled manner, turning on during active illumination phases and turning off during detection phases. This periodic activation pattern enables the system to collect reflection data during off-phases and transparency data during on-phases, resolving the contradiction between detecting different surface types with a single sensor system.
2Reliability
If active illumination is used to detect transparent surfaces, then detection capability improves, but harmful factors increase due to glare and false reflections
Solution Approach 1:
The system applies preliminary anti-action by turning off the LEDs during detection phases specifically to prevent glare and false reflections from compromising measurement accuracy. This proactive measure eliminates the harmful effects before they can interfere with the detection process.
Solution Approach 2:
The system performs preliminary action by activating LEDs in controlled phases before detection, allowing the environment to settle and reducing spontaneous reflections. The structured illumination timing ensures that detection occurs during stable conditions with minimal glare interference.
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 approach enhances the accuracy of occupancy maps, improves navigation by correctly identifying reflective surfaces, and reduces collision risks, enabling the AMD to safely and effectively move within environments with various reflective obstacles.
Implementation Method 1
Reflective surfaces such as glass, polished glass or stone, mirrors, and so forth may reflect images of another portion of the physical space
Implementation Method 2
at a fourth time, a fourth image is acquired with the first camera while the first lighting component is turned off... based at least in part on the first image and the fourth image, a distance to the surface is determined
Implementation Method 3
using stereovision or ultrasound to determine distance and orientation of reflective surfaces
Data Source
AI summary
An autonomous mobile device (AMD) in a physical space uses its own reflection to detect and map reflective surfaces. A first image is acquired by a camera of the AMD at a first time while a light on the AMD is turned on. The first image is processed to find a candidate reflection, characterized by a bright spot in the image. A second image is acquired at a second time while the light is off. The reflection is confirmed by absence of the candidate reflection in the second image. A display on the AMD presents a displayed image at a third time. A third image acquired during the third time is processed to find the features of the displayed image. Once found, a location and orientation in physical space of a plane of the surface causing the reflection is calculated. An occupancy map is updated to include this information.