Motor Control for Self-Calibrating Multi-Camera Alignment
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Solution Overview
Problem
Machine vision vehicle alignment systems require real-time alignment reading responses and need to track vehicle-mounted targets quickly and smoothly to maintain an optimal field of view, while also ensuring safety and extending the system's functional life through optimal operation and component diagnostics.
Innovation Solution
A vehicle alignment system with autonomous camera pods on tracks, where data processors determine optimal camera positions based on image data and send motor commands to move the pods, ensuring continuous tracking and safety features like automatic movement stoppage upon resistance detection, along with diagnostics for extended component life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If cameras are rigidly connected to maintain fixed position and orientation, then system stability is improved, but system adaptability deteriorates
Solution Approach 1:
The patent transitions from rigid, fixed camera mounting to dynamic, movable camera pods that can autonomously adjust their positions along tracks. The camera pods are equipped with motor drives that enable real-time movement to track vehicle targets, transforming the static camera system into a dynamic one that adapts to changing alignment requirements while maintaining operational stability through controlled motion.
2Adaptability or versatility
If separate camera/target systems are used for continuous calibration, then system adaptability is improved, but device complexity increases
Solution Approach 1:
The patent combines the calibration target with the vehicle targets into a single integrated target system. The calibration target is mounted on the vehicle alongside the alignment targets, allowing the same target structure to serve dual purposes: providing calibration reference points for determining camera pod positions and serving as the alignment measurement target. This eliminates the need for separate calibration apparatus and reduces system complexity.
Solution Approach 2:
The camera pods perform multiple functions using the same hardware components. The primary cameras capture both calibration target images and vehicle target images, while the motor drives enable both positioning for calibration and tracking for alignment measurement. This multi-functionality reduces the need for dedicated calibration equipment and simplifies the overall system architecture.
3Speed
If cameras continuously track vehicle targets in real-time, then alignment reading response speed is improved, but processing time increases
Solution Approach 1:
The system performs preliminary calibration by capturing images of the calibration target to determine camera pod positions before proceeding with vehicle alignment measurement. This pre-positioning ensures that when vehicle targets are captured, the camera pods are already optimally positioned, reducing the need for time-consuming adjustments during the actual alignment process and improving overall response speed.
Solution Approach 2:
The camera pods autonomously determine their own positions and movement requirements by processing images of the calibration target and vehicle targets independently. Each camera pod with its integrated processor self-calibrates and self-positions without requiring centralized control coordination, reducing communication overhead and processing delays in the system.
4Ease of operation
If motor drives are used to move camera pods autonomously, then tracking smoothness is improved, but system reliability requirements increase
Solution Approach 1:
The system implements feedback control where camera pods continuously capture images of the calibration target and vehicle targets, process this visual information to determine their current positions and optimal locations, and use this feedback to control motor drive movements. This closed-loop feedback ensures smooth, accurate tracking while the system monitors for abnormal conditions such as excessive current draw that would indicate user contact or mechanical issues.
Data Source
AI summary
Embodiments include a method for autonomous camera pod tracking of a vehicle during vehicle alignment. The method can include receiving, at a processor of an autonomous camera pod, at least one of vehicle target image data from a vehicle target camera or calibration target image data from a calibration camera, the vehicle target camera being adapted to acquire images of a target mounted to the vehicle, and the calibration camera being adapted to acquire images of a calibration target mounted to a sister autonomous camera pod. An optimal location of the autonomous camera pod can be calculated based on the received vehicle target image data or calibration target image data. The method can include transmitting, when it is determined to move the autonomous camera pod, a motor command to a motor drive of the autonomous camera pod, thereby causing the autonomous camera pod to move to the optimal location.