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Research Studentship in Mobile Robot Navigation and Mapping

Research Studentship in Robotics

Project: Mobile Robot Navigation and Mapping

3.5-year DPhil studentship 

Supervisors: Prof Maurice Fallon

Mobile robot navigation is a crucial capability which allows a robot to understand its environment and its own movement and to move safely around obstacles and people using real-time sensor processing and map building. In the Dynamic Robot Systems (DRS) Group we focus on mapping, reconstruction and sensor fusion to build rich 3D representations around robots moving quickly and dynamically --- such as quadrupeds and flying robots.

This studentship is open to students interested in the following research topics in the field of mobile robot navigation: multi-sensor odometry, simultaneous localisation and mapping (SLAM), efficient path planning, place recognition, reconstruction as well as other related topics.

Algorithms will be demonstrated using robots navigating in nuclear facilities, forests (see and on construction sites – such as our ANYmal and Spot robots as well has sensor systems developed in our group.

The student will join the DRS group which is part of Oxford Robotics Institute (ORI). The research environment in ORI will expose the student to a wide variety of robotics research fields such as mobile and soft robotics, autonomous vehicles and manipulation with a focus on the underpinning scientific topics. ORI’s research is supported by professional engineering team which will allow the student to demonstrate their work in a real-world test environments.


This studentship is funded through the UK Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership and is open to Homestudents (full award – home fees plus stipend). Full details of the eligibility requirements can be found on the UK Research and Innovation website.

There is flexibility to partly support international students with this studentship. Please contact the supervisor to discuss this detail.

Award Value

Course fees are covered at the level set for Home students (c. £8965 p.a.). The stipend (tax-free maintenance grant) is c. £17,668 p.a. for the first year, and at least this amount for a further two and a half years. 

Candidate Requirements

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

A first class honours degree in Engineering, Computer Science or related disciplines
Excellent English written and spoken communication skills
Experience developing algorithms for robotic perception, signal processing, and computer vision

The following skills are desirable but not essential:

Ability to programme in C++ or Python. Other desirable languages/tools include Matlab and the Robot Operating System (ROS)
Experience working with mobile robots
Experience practically using machine learning for sensor processing

Application Procedure

Informal enquiries are encouraged and should be addressed to Prof Maurice Fallon (

Information about the research in the DRS group can be found here:

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 23ENGIN_MF in all correspondence and in your graduate application.

Application deadline: noon on 9 December

Start date: October 2023