Level: MSc
Project Description
This MSc project aims to design and implement a novel pose estimation algorithm that leverages low-cost sensors, such as ultra-wideband and/or Bluetooth Angle of Arrival (AoA) technology, combined with a filter, such as an Extended Kalman Filter (EKF), for accurate and robust relative pose estimation across multiple robots within a swarming configuration. This will be achieved by using appropriate transceivers on multiple robotic test platforms, as well as multiple transmitters, placed strategically within the testing volume. The sensor information will then be fused using the EKF (or equivalent filter) in order to give an accurate estimate of the robots’ relative and absolute positions. The system will provide a cost-effective alternative to traditional localisation approaches, such as using GPS or a motion capture system, while offering the advantages of wireless technology and advanced state estimation techniques. The end goal of this project will be to enable a scalable means for swarm-based aerial robotic applications.
Objectives
- Investigate the state-of-the-art in low-cost localisation, such as Bluetooth AoA technology, ultra-wideband, and its applications in localisation.
- Develop a mathematical model for the sensor-based swarm.
- Design and implement an appropriate filtering algorithm for fusing relevant data.
- Create a prototype of the swarm-based localisation using off-the-shelf hardware and custom software.
- Evaluate the system's performance in terms of accuracy, latency, and robustness compared to existing motion capture solutions.
- Write-up of dissertation and conference/journal paper.
Expected Outcomes
- A functional prototype of the swarm-based setup.
- Comprehensive analysis of the system's performance and limitations.
- Comparison with existing localisation technologies.
- Documentation of the design process, algorithms, and implementation details.
- Recommendations for future improvements and potential applications.
Relevant Skills
- Background in signal processing and state estimation techniques.
- Proficiency in programming (Python, MATLAB, or similar languages).
- Familiarity with wireless communication protocols.