Object Recognition Using Dual Light Patterns for Low-Energy Ranging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing object recognition systems require high energy consumption to scan a space with light, and they often struggle to simultaneously recognize objects at both short and long distances efficiently.
Innovation Solution
The system employs a light source that emits first and second light beams with different spatial distributions, allowing the photodetector device to detect reflected light from both beams in the same exposure period. This configuration enables the recognition of objects and the derivation of their distances using a signal processing circuit and an object recognition model pre-trained by machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If light beams are emitted to cover the entire scene for object recognition, then recognition coverage is improved, but energy consumption increases
Solution Approach 1:
The light emission is segmented into multiple sequential patterns rather than continuous full-scene illumination. The light source emits light in different spatial distributions at different time periods, dividing the recognition task into segments that collectively cover the scene while reducing instantaneous energy requirements.
Solution Approach 2:
The system employs periodic light emission with varying spatial distributions. Different light patterns are emitted in alternating time periods, creating a periodic action that enables comprehensive scene coverage over time while maintaining lower average energy consumption compared to continuous full-scene illumination.
2Adaptability or versatility
If multiple light beams are emitted to recognize objects at both short and long distances, then recognition capability is improved, but processing time increases
Solution Approach 1:
Different light patterns optimized for different distance ranges are emitted in alternating time periods. This periodic emission strategy enables the system to gather information from both short and long distances through multiple patterns while reducing the total processing time compared to sequentially acquiring all distance information with a single pattern.
Solution Approach 2:
The system performs preliminary light emission with different spatial distributions to gather information about objects at various distances. By pre-emitting multiple light patterns with different coverage characteristics, the system prepares data that can be processed more efficiently to achieve both recognition and ranging.
3Use of energy by moving object
If sparse light beams are emitted to reduce energy usage, then energy consumption is reduced, but measurement precision may deteriorate
Solution Approach 1:
The sparse light emission is segmented into multiple patterns with different spatial distributions. Each individual pattern uses sparse illumination to reduce energy consumption, but the collection of segmented patterns collectively provides sufficient information for accurate object recognition and ranging through complementary coverage.
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 reduces energy usage by emitting sparse light beams that do not need to cover the entire scene, while simultaneously enabling efficient recognition and ranging of objects at both short and long distances, thereby reducing overall processing time.
Implementation Method 1
a photodetector device (150), each element of which outputs photodetection data responsive to the amount of light that is incident on each element during a specified exposure period
Data Source
AI summary
An object recognition apparatus includes a light source, an image sensor, a control circuit, and a signal processing circuit. The control circuit causes the light source to emit first light toward a scene and subsequently emit second light toward the scene, the first light having a first spatial distribution, the second light having a second spatial distribution. The control circuit causes the image sensor to detect first reflected light and second reflected light in the same exposure period, the first reflected light being caused by reflection of the first light from the scene, the second reflected light being caused by reflection of the second light from the scene. The signal processing circuit recognizes an object included in a scene based on photodetection data output from the image sensor, and based on an object recognition model pre-trained by a machine learning algorithm.