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Automated Delivery of Microfabricated Targets for Intense Laser Irradiation Experiments

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Optimizing success rate with Nonlinear Mapping Control in a high-performance raspberry Pi-based light source target

Guiyu Zhou¹, Bo Zhang^1,2, Qinghao Li³

¹School of Electronic Information and Engineering, Yibin University, Yibin, China.

|February 25, 2025

Summary

This summary is machine-generated.

This study introduces a nonlinear mapping control method to improve 2D gimbal control for moving target tracking. The new system significantly enhances tracking accuracy and response speed, achieving a 100% success rate.

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Area of Science:

Robotics and Control Systems
Computer Vision
Mechatronics

Background:

Linear mapping in 2D gimbal control for moving target tracking suffers from significant control errors and slow response times.
Existing systems struggle with real-time tracking accuracy, particularly for dynamic targets like light sources.

Purpose of the Study:

To develop and evaluate a nonlinear mapping control method to overcome the limitations of linear mapping in 2D gimbal control.
To enhance the success rate and accuracy of light source target tracking systems.
To optimize system performance by balancing response speed and stability through parameter adjustment.

Main Methods:

Implemented a real-time recognition system using Raspberry Pi 4B and OpenCV for rectangular frames and laser spot images.
Utilized an OpenMV H7 Plus camera integrated into the tracking system to capture and process laser spot paths.
Connected the control system to an STM32F407ZGT6 microcontroller for precise driving of a 42-step stepper motor.
Optimized system performance by adjusting the parameter 'c' of the nonlinear mapping curve.

Main Results:

Achieved a significant improvement in control accuracy for the target tracking system.
Recorded a miss rate of 3.3% and an average error rate of 0.188% at a distance of 1.25 meters.
Demonstrated a 100% success rate in real-time target tracking using the proposed nonlinear mapping control method.

Conclusions:

The proposed nonlinear mapping control method effectively addresses the limitations of linear mapping in 2D gimbal control.
The system shows substantial advancements in real-time tracking and control, offering improved accuracy and response.
The method has potential for broader applications in intelligent control fields requiring precise real-time tracking.