Semantic based onboard UAV navigation

In recent years the field of robotic navigation has increasingly harnessed semantic information in order to facilitate the planning and execution of robotic tasks. The use of semantic information focuses on employing representations more understandable by humans to accomplish tasks with robustness against environmental change, limiting memory requirements and improving scalability. Contemporary computer vision algorithms extracting semantic information have continuously improved their performance on benchmark datasets, however, most computations are expensive, limiting their use for robotic platforms constrained by size, weight and power such as unmanned aerial vehicles (UAVs). Recent advances have demonstrated the potential for navigation systems based on semantic information to be included into real-time operation of UAVs. This PhD focuses on the development and incorporation of semantic information into a UAV navigation system.


Chief Investigators