Study level
- PhD
Faculty/School
Faculty of Engineering
Topic status
We're looking for students to study this topic.
Supervisors
- Position
- Professor
- Division / Faculty
- Faculty of Engineering
Overview
Making a robot understand what it sees is one of the most fascinating goals in our current research. To this end, we develop novel methods for Semantic Mapping and Semantic SLAM by combining object detection with simultaneous localisation and mapping (SLAM) techniques.
We work on novel approaches to SLAM that create semantically meaningful maps by combining geometric and semantic information. Such semantically enriched maps will help robots understand our complex world and will ultimately increase the range and sophistication of interactions that robots can have in domestic and industrial deployment scenarios.
If you are interested in tightly combining modern deep learning and computer vision approaches with classical probabilistic robotics, this topic is for you. Our PhD topics give you the opportunity to investigate how to use recent implicit representations (such as NERFs) to represent scenes and objects, and how to use such scene representations for navigation but also for robotic learning for mobile manipulation.
Contact
Contact the supervisor for more information.