3D Position Detection Using Multi-Sensor Distance Data Fusion
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Solution Overview
Problem
Existing position detection systems using LiDAR devices or stereo cameras struggle to identify the position of an object when an obstacle is present between the detection device and the object.
Innovation Solution
A position detection system comprising multiple distance detection apparatuses that generate distance data by detecting light reflected from an object, an object identification part that identifies the object within the distance data, and a position identification part that determines the object's position in a three-dimensional space by combining data from multiple apparatuses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single distance detection apparatus is used to detect object position, then the device complexity is low, but the position detection reliability deteriorates when obstacles are present
Solution Approach 1:
The system divides the detection task into multiple independent distance detection apparatuses positioned at different locations. Each apparatus independently detects distance data, and the object identification part segments the distance data to identify which apparatus detected the target object. This segmentation allows the system to maintain high reliability by having multiple detection paths while keeping each individual apparatus relatively simple.
Solution Approach 2:
The system merges the detection results from multiple distance detection apparatuses by integrating their distance data through the object identification part and position identification part. The position identification part combines the position information from multiple apparatuses to determine the final object position, thereby improving overall detection reliability through data fusion while managing device complexity through systematic integration.
2Reliability
If multiple distance detection apparatuses are deployed to detect object position, then the position detection reliability improves, but the device complexity increases
Solution Approach 1:
The object identification part and position identification part serve as universal processing components that handle data from multiple different distance detection apparatuses. These components perform multiple functions: identifying the target object across different data sources, determining positions from multiple apparatuses, and integrating results. This multi-functionality reduces overall system complexity by using shared processing logic rather than dedicated processing for each apparatus.
Solution Approach 2:
The object identification part acts as an intermediary between the multiple distance detection apparatuses and the position identification part. It receives distance data from various apparatuses, identifies which data corresponds to the target object, and passes relevant information to the position identification part. This intermediary layer simplifies the architecture by centralizing the complexity of multi-apparatus coordination in a dedicated component.
3Measurement precision
If distance data from multiple apparatuses is integrated to identify object position, then the measurement precision improves, but the loss of time increases due to data processing
Solution Approach 1:
The object identification part performs preliminary action by pre-identifying which distance data corresponds to the target object before the position identification part processes the position information. This preliminary identification filters out irrelevant data early in the process, reducing the amount of data that requires complex integration and position calculation, thereby minimizing processing time while maintaining measurement precision.
Solution Approach 2:
The system skips unnecessary processing steps by directly identifying the target object in the distance data and immediately proceeding to position calculation. The object identification part quickly determines which apparatus detected the target and extracts only the relevant distance data, rushing through the identification phase to minimize the time spent on data integration and enable faster position measurement.
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 accurate identification of an object's position in a three-dimensional space even when obstacles are present, by integrating data from multiple distance detection apparatuses.
Implementation Method 1
distance data indicating distances to a plurality of positions on the object by detecting light reflected by the object
Data Source
AI summary
A position detection system includes: a plurality of distance detection apparatuses that generate distance data indicating distances to a plurality of positions on the object by detecting light reflected by the object in a predetermined three-dimensional space; an object identification part that identifies the object included in one or more pieces of distance data among a plurality of pieces of the distance data generated by the plurality of distance detection apparatuses; and a position identification part that identifies a position of the object in the three-dimensional space on the basis of (i) a position in the three-dimensional space of the distance detection apparatus that generated the distance data with which the object identification part identified the object and (ii) a position of the object in the distance data.