Project Description:
Magnetic Coupling Localization (MCL) is a promising technique for tracking wireless microrobots in real-time, even in environments where ultrasound (US) localization is unreliable due to wave reflectors. This project aims to improve the accuracy, robustness, and real-time performance of MCL by refining the localization algorithm and testing its effectiveness in different conditions. The student will implement and evaluate improvements in signal processing, fusion techniques, and experimental validation.
Research Objectives:
- Improve the accuracy and robustness of MCL under various conditions.
- Investigate the effect of external disturbances and motion dynamics on localization performance.
- Optimize real-time implementation for improved responsiveness and lower latency.
- Compare MCL performance with alternative localization methods, such as ultrasound imaging.
Key Tasks:
- Literature Review: Study existing localization techniques for wireless microrobots, with a focus on MCL and data fusion approaches.
- Algorithm Development: Improve the current MCL algorithm by optimizing filtering techniques (e.g., Kalman filtering, adaptive filtering) and handling data interruptions.
- Simulation & Validation: Implement the refined algorithm in simulation software (e.g., MATLAB, Python) and test it under different conditions.
- Experimental Work: Conduct physical experiments using a wireless microrobot setup to validate the improved localization method.
- Performance Evaluation: Compare MCL results against ground truth data and alternative localization methods.
