Remote Moving-Object Control Using 3D Point Cloud Matching
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Solution Overview
Problem
Existing technologies for detecting the position of a moving object require a long processing time due to sequential scanning after positioning a two-dimensional model, which hinders efficient recognition and control.
Innovation Solution
A remote control device that acquires three-dimensional point cloud data using a distance measuring device, estimates the position and orientation of a moving object by matching a template point cloud, and generates control commands to quickly detect the object's position by determining an optimal start position for matching, utilizing actuator drive history, previous matching positions, and target routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sequential scanning is performed after positioning a two-dimensional model at the leading point of projected images, then the matching process can be systematically executed, but the processing time becomes excessively long
Solution Approach 1:
The patent applies preliminary action by performing several preparatory steps before the actual template matching: (1) Acquiring three-dimensional point cloud data in advance, (2) Converting it to two-dimensional projected images beforehand, (3) Determining the start position of scanning in advance using actuator drive history and previous matching positions. These preliminary actions ensure that when matching begins, all necessary data and calculations are already prepared, enabling faster processing while maintaining accuracy.
Solution Approach 2:
The patent replaces the traditional mechanical sequential scanning approach with an optimized computational method. Instead of blindly scanning from a fixed leading point, the system uses actuator drive history and previous matching positions to calculate and jump directly to the optimal start position, substituting computational intelligence for brute-force mechanical scanning.
2Reliability
If the start position of matching is set far from the moving object to ensure complete coverage, then all possible positions can be searched, but the matching process takes longer to complete
Solution Approach 1:
The patent implements feedback by continuously using the results of previous matching operations and actuator drive history to inform the selection of the start position for the current matching operation. The system feeds back the movement information and previous position data to dynamically adjust and optimize the scanning start position, ensuring both completeness and efficiency.
Solution Approach 2:
The patent applies dynamics by making the start position adaptive and dynamic rather than fixed. The start position changes based on real-time actuator drive history and previous matching results, allowing the system to dynamically adjust its search strategy to match the actual movement patterns of the target object.
3Adaptability or versatility
If three-dimensional point cloud data is processed using traditional two-dimensional image matching methods, then compatibility with existing systems is maintained, but processing efficiency is reduced
Solution Approach 1:
The patent applies dimensionality change by converting three-dimensional point cloud data into two-dimensional projected images, allowing the use of established two-dimensional template matching algorithms. This dimensional transformation maintains compatibility with existing 2D image processing systems while enabling efficient processing of 3D data through the intermediate 2D representation.
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 significantly reduces the processing time required for template matching, enabling faster and more accurate detection of moving objects by setting the start position near the object's likely location, thereby improving detection efficiency.
Implementation Method 1
acquiring three-dimensional point cloud data measured using a distance measuring device
Data Source
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AI summary
A remote control device (300) includes, at least one processer configured to perform processes including, acquiring three-dimensional point cloud data measured using a distance measuring device (80), estimating at least one of a position and an orientation of a moving object (100) in the three-dimensional point cloud data by matching a template point cloud indicating the moving object (100) with the three-dimensional point cloud data, determining a start position to start matching of the template point cloud with the three-dimensional point cloud data; and generating a control command for remotely controlling the moving object (100) using at least one of the estimated position and the estimated orientation of the moving object (100) and transmit the control command to the moving object (100).