Project Title Intelligent Multi-Sensor Fusion Schemes for Environment-Aware UAV Applications
Start Date May 01, 2020
End Date Oct 31, 2023
Nationality Requirements on Candidate(s): Applicants should be Malaysian citizens
Minimum requirements: Outstanding mathematical background and a first class honours degree (or equivalent) from top-tier universities. Strong English writing and programming skills as well as in-depth machine learning knowledge are also highly recommended.
Details: Upon successful completion of the study, PhD degree will be awarded by the University of Southampton, UK. The candidate will be supervised by ASSOCIATE PROF. DR. Won SeungHwan, ASSISTANT PROF. DR. Ling Ting Yang, and an academic from the UK campus during his or her study. The candidate will have the opportunity to spend part of the PhD in the UK campus.
Autonomous navigation of Unmanned Aerial Vehicle (UAV) plays an essential role in designing robust industrial UAVs for various applications. One interesting application is the ability to navigate indoors and under tree canopies. Such drones will be extremely valuable for security and data collection in farms or plantations. Recently, diverse sensors and multi-sensor fusion algorithms have been proposed for such applications, however, most approaches are vision-based, which enables to restrict a potential on the multi-sensor fusion approaches. For this ambitious project, a successful candidate will be designing a novel multi-sensor fusion algorithms based mainly on Deep Learning (DL) algorithms, which supports obstacle avoidance and situational awareness in a commercial drone frame exploiting multiple environmental sensors to reinforce the vision aided system. More explicitly, the approach will be based on a promising crossing between Bayesian inference and DL, providing reliable uncertainty estimates by leveraging the hierarchical representation capability of DL approach, which can also suggest a higher level of autonomous navigation capability. This will enhance the drone’s autonomous navigation capability even in unexpected environments. Accordingly, our project referred to as “Intelligent Multi-Sensor Fusion Schemes for Environment-Aware UAV Applications” enables to manifest a unique opportunity of gaining the cutting edge technology in diverse manners. Again, the candidates having prior experiences in embedded programming, silicon Radar, Lidar, or machine learning background are encouraged to apply.
Benefits: In addition to tuition fees exemption, a monthly stipend of RM2,300 will be available during Malaysian residence period (up to three and half years). Similarly, a monthly stipend during UK residence period (three to six months) will also be available (a reasonable allowance will be given.).
For application, please send your CVs, transcript and certificates in a single PDF file to email@example.com
Only short-listed candidates will be contacted for interviews.