Research Supervisor Connect
This project investigates advanced indoor positioning systems using mobile robots equipped with UWB, mmWave, THz, or WiFi technologies to achieve high-precision localisation. The research focuses on developing novel algorithms and sensing techniques to enable robust, real-time, and scalable positioning in complex indoor environments.
Electrical and Computer Engineering
The project aims to overcome the limitations of GPS-denied environments by leveraging advanced wireless sensing and localisation methods. By integrating high-resolution wireless signals with mobile robotic platforms, the research will explore time-of-flight, angle-of-arrival, and channel state information (CSI)-based methods for precise positioning. Machine learning and sensor fusion approaches will be incorporated to enhance robustness against multipath, interference, and non-line-of-sight (NLOS) conditions commonly encountered indoors. The project will involve both simulation studies and experimental validation using robotic testbeds, with applications in autonomous navigation, asset tracking, smart buildings, industrial automation, and healthcare monitoring. The outcomes are expected to provide a foundation for next-generation positioning systems with centimeter-level accuracy, adaptability, and scalability.
Research Techniques/Methodologies/Technologies
The project will use wireless localisation techniques such as time-of-flight, angle-of-arrival, and CSI-based methods, along with advanced signal processing, machine learning, and multi-sensor fusion. Robotic platforms and software-defined radios (SDR) will be employed for real-world prototyping and testing.
Successful candidates
Candidates should have a strong background in wireless communications, robotics, signal processing, or related fields. Proficiency in programming (Python, MATLAB, or C/C++) and familiarity with robotic systems, localisation algorithms, or RF hardware are highly desirable. The ideal candidate should be motivated, possess strong problem-solving skills, and demonstrate the ability to work across interdisciplinary domains involving robotics and wireless sensing.
How to apply:
To apply, please email [email protected] the following:
The opportunity ID for this research opportunity is 3699