PhD Studentship : Research Studentship in Multi-Sensor Mapping and Spatial AI

3.5-year DPhil studentship

Supervisor: Prof Maurice Fallon

Localisation and mapping are two key capabilities for mobile robots. By combining sensor inputs from cameras, lidars and motion sensors the challenge is to estimate an accurate motion trajectory in real-time while also reconstructing the robot’s environment. Solving this challenge enables obstacle avoidance, motion planning and higher level autonomy.

The DPhil student will contribute to a collaborative project called “Harmonic Space” funded by the National Research Foundation of Korea. Collaborators in the project include Prof. Ayoung Kim (Seoul National University) and Prof. Luca Carlone (MIT) including potential research visits. The ‘Harmonic Space’ project will develop new methods to build 3D maps with greater fidelity, to determine how to detect change over time, and develop methods to understand and segment these maps using spatial AI technologies such as neural representations (NeRF and Gaussian splatting), scene graphs and visual language models (VLMs).

The precise research topic for this DPhil student is open for discussion and can be defined in conversation with the DPhil supervisor (Prof. Maurice Fallon).

Eligibility

This studentship is funded by the National Research Foundation of Korea through the Harmonic Space project and is open to Home (fully funded) or Overseas students (partial funding).

Award Value

Course fees will be covered at the level set for Home/ROI students and a stipend (tax-free maintenance grant) will be paid at the UKRI rate (at least £19,237 p.a.).

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

• A first class honours or strong upper second-class undergraduate degree in Engineering or Computer Science
• Excellent English written and spoken communication skills
• Knowledge of robotic sensing and mapping techniques
• Programming skills (C++ and scripting languages)

The following skills are desirable but not essential:

• A distinction or first class honours masters degree in Engineering or Computer Science
• Previous research experience in the area of robotics or computer vision (e.g., final year project, internship)

Application Procedure

Informal enquiries are encouraged and should be addressed to Prof Maurice Fallon (mfallon@robots.ox.ac.uk)

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website.

Please quote 25ENGIN_MF in all correspondence and in your graduate application.

Application deadline: noon on 3 December 2024 (In line with the University admissions deadline set by the University)

Start date: October 2025

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