Air-flow sensing for applications in autonomous driving

Organization
Software Engineering and Information Systems
Abstract
Summary:
Establishing of a state of the art of fluid flow sensing in robotics, and investigating its applications in autonomous driving using computational-fluid-dynamics simulations.
Keywords:
Perception, flow sensing, autonomous robotics, computational fluid dynamics
Skills required and developed:
fluid-flow sensing, computational-fluid-dynamics simulation, data processing
Description:
Sensing of fluid flow has gotten increased attention of underwater robotics community in the last decade. The field fluid flow has also been of interest in aerial robotics. It has however not been investigated much in the field of autonomous ground robotics to that extent.
The project aims to:
1.\tEstablish a state of the art for fluid flow sensing in robotics (aerial, underwater as well as ground robotics).
2.\tInvestigate potential uses of air-flow sensing in autonomous driving.
3.\tValidate potential applications of air-flow sensing in autonomous driving using computational-fluid-dynamics (CFD) simulations.

Some relevant literature:
[1] Juan F. Fuentes-Pérez, Jeffrey A. Tuhtan, Gert Toming, Maarja Kruusmaa, Naveed Muhammad, Ruth Carbonell-Baeza, Mark Mussal, "Map-based localization in structured underwater environment using simulated hydrodynamic maps and an artificial lateral line", IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, 2017.
[2] Naveed Muhammad, Juan F. Fuentes-Pérez, Jeffrey Tuhtan, Gert Toming, Mark Musall, Maarja Kruusmaa, "Map-based localization and loop-closure detection from a moving underwater platform using flow features", Autonomous Robots, 43(6), 1419-1434.
[3] V. H. Bennetts, T. P. Kucner, E. Schaffernicht, P. P. Neumann, H. Fan and A. J. Lilienthal, "Probabilistic Air Flow Modelling Using Turbulent and Laminar Characteristics for Ground and Aerial Robots," in IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 1117-1123, April 2017. doi: 10.1109/LRA.2017.2661803
Graduation Theses defence year
2019-2020
Supervisor
Yar Muhammad
Spoken language (s)
English
Requirements for candidates
Level
Bachelor, Masters
Keywords
#Perception, flow sensing, autonomous robotics, computational fluid dynamics

Application of contact

 
Name
Yar Muhammad
Phone
E-mail
Yar.Muhammad@ut.ee
See more
https://sep.cs.ut.ee/Main/StudentProjects2019#Yar