| Building: | Mackenzie, Room 3244 |
| Department: | Mechanical and Aerospace Engineering |
| Degrees: | Degrees: B.Sc. (Mechatronics), M.Sc. (Systems & Control), and Ph.D. (Robotics & Control); Ph.D., P.Eng., SMIEEE |
| Website: | https://carleton.ca/rncsl/ |
About
Dr. Hashim Mohamed is currently (Jan.2022-Present) an Assistant Professor at the Department of Mechanical and Aerospace Engineering at Carleton University, Ottawa, Ontario, Canada. He is the founder and director of the Robotics, Navigation, and Control Systems Laboratory (RNCSL). Between Aug.2019 and Dec.2021 he was an Assistant Professor at the Department of Engineering & Applied Science at Thompson Rivers University (TRU), Kamloops, British Columbia, Canada. He is a registered Professional Engineer (P.Eng.) in the province of Ontario, Canada, and a senior member of IEEE.
Education
- Ph.D. degree in Robotics and Control,
Department of Electrical and Computer Engineering,
Faculty of Engineering,
Western University (UWO). - M.Sc. degree in Systems and Control Engineering,
Department of Control & Instrumentation Engineering (CIE),
College of Engineering and Physics,
King Fahd University of Petroleum and Minerals (KFUPM). - B.Sc. degree in Mechatronics,
Department of Mechanical Engineering,
Faculty of Engineering,
Helwan University (HU).
Research Interests
The ultimate goal of my research is to develop novel technologies related to: Perception and Navigation, Control, and Trajectory Planning. I aspire to discover new ways to improve the performance of dynamical systems, in particular smart systems which include semi-automated and fully autonomous systems, such as unmanned aerial vehicles (UAVs/drones), autonomous underwater vehicles (AUVs), mobile robots, satellites, and other robotics applications. My research interests include but are not limited to
- Guidance, Perception & Navigation, and Control.
- Vision-aided inertial navigation systems for UAVs/drones and ground/mobile robots,
- Robot localization and mapping with inertial units,
- Filtering and estimation techniques: stochastic and deterministic,
- Sensor fusion,
- Relative localization and collaborative/distributed control of multi-agent systems,
- Artificial intelligence (Supervised Learning, Unsupervised, and Reinforcement Learning),
- Optimization techniques and metaheuristic algorithms (single and multi objective)
The complete research profile can be found in GoogleScholar
