Vehicle Remote Control Switching for Defective Assembly Detection
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Solution Overview
Problem
Existing technologies face challenges in maintaining accurate detection of a vehicle's position and orientation for remote control, especially when there is defective assembly of components.
Innovation Solution
A control device that employs different methods for determining the position and orientation of a vehicle based on the assembly status of its components, using machine learning models or 3D CAD data, to maintain detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single detection method is used for all assembly conditions, then the system is simple to operate, but detection accuracy decreases when components are defectively assembled
Solution Approach 1:
The system dynamically switches between a first detection method (for correctly assembled vehicles) and a second detection method (for defectively assembled vehicles) based on assembly condition determination. This dynamic adaptation maintains high detection accuracy across different assembly conditions while managing system complexity through conditional logic.
Solution Approach 2:
The system changes the detection parameters and methods based on the determined assembly condition. When defective assembly is detected, the system switches to an alternative detection method with different parameters, allowing accurate position and orientation detection regardless of assembly quality.
2Measurement precision
If different detection methods are used based on assembly status, then detection accuracy is maintained, but the control system becomes more complex
Solution Approach 1:
The detection system is segmented into multiple specialized methods: a first detection method optimized for correctly assembled vehicles and a second detection method optimized for defectively assembled vehicles. The determination unit segments the control flow by routing to the appropriate detection method based on assembly condition, maintaining accuracy while managing complexity through structured division.
Solution Approach 2:
The system creates alternative detection pathways (copies of detection logic) that are activated based on assembly conditions. Instead of modifying a single detection method, the system maintains separate detection routines for different assembly states, allowing each to be optimized independently for its specific condition.
3Ease of operation
If external sensors are used to detect vehicle position and orientation, then remote control is enabled, but detection accuracy decreases with defective component assembly
Solution Approach 1:
The system uses feedback from the determination unit about assembly conditions to adjust the detection strategy. External sensor data is processed differently based on whether components are correctly assembled, with the system adapting its interpretation and processing of sensor signals to maintain accuracy despite assembly variations.
Solution Approach 2:
The detection system dynamically adapts its processing based on real-time determination of assembly conditions. When defective assembly is detected, the system switches to alternative processing logic that compensates for the expected geometric deviations, maintaining remote control capability while preserving detection accuracy.
Data Source
AI summary
A control device for remotely controlling a vehicle in a factory where a plurality of processes are performed for manufacturing a vehicle includes: a determination unit that determines whether or not a component is correctly assembled to the vehicle; and a computing unit that, when the component is correctly assembled to the vehicle, acquires at least one of a position and an orientation of the vehicle using a first method based on detection data acquired by an external sensor, and, when the component is not correctly assembled to the vehicle, obtains at least one of a position and an orientation using a second method different from the first method based on the detection data.