To prospective graduate students: The FSC group welcomes passionate and dedicated bright minds to join us in a stimulating and nurturing environment. Please follow the UTIAS admissions guidelines to apply for our graduate programs and please specify our research field of “Aircraft Flight Systems and Control” on your application file, so that your application will be screened. All reviewed applicants will be contacted individually by Professor Liu to follow up with an interview or to receive feedback. Students pursuing PhD programs will be considered with priority.
Prospective graduate students are also encouraged to check the FSC group’s research theme (link tbd) and recent research projects to align their research interests in the research statement of the application. Each graduate student for the MASc or PhD program will determine their individual research topics mutually by working together with Professor Liu upon enrolment. Sometimes, the FSC may post specific research topics here for the upcoming admission cycle.
MASC/PhD (2026 admission) Research Topics
(no topics posted at this time)
To registered M.Eng. Students: Are you an M.Eng. student searching for a meaningful project aligned with cutting-edge aerospace technologies? The FSC group routinely offers a number of project topics that align with the M.Eng. course project requirements and guidelines. The posted M.Eng. project topics are expected to carry out in one semester. Interested M.Eng. students are encouraged to contact Professor Liu directly to inquire about these topics within the specified timeframe. The projects are assigned on a first-come-first-served basis.
MENG Project Topics (Winter/Summer of 2026)
The following project topics are available for registered (UTIAS) M.Eng. students. The inquiry/application deadlines are: January 15th (for winter semester) and April 15th (for summer semester). Please contact Professor Liu by email with your CV and up-to-date transcripts. Interested M.Eng. Students of other departments/institutions please contact Professor Liu directly.
[ME1]: Aerial Manipulator Modelling (supervisor: Professor Liu, collaborator: Dr. Longhao Qian)
Aerial manipulation has become an active research area in both academia and industry. It holds significant potential for enabling a wide range of tasks, including high-rise window cleaning, construction, and aerial transportation. Developing a high-fidelity simulation tool is essential for validating intelligent control and planning algorithms for these applications. This project aims to build a high-fidelity physics simulation environment using NVIDIA Isaac Sim to perform quadrotor software-in-the-loop (SITL) simulations with robotic arms. Beyond basic SITL capabilities, the project also investigates detailed physical interactions between objects and robotic manipulators—such as collision dynamics, friction, and inertia effects—to evaluate the control performance of aerial manipulation systems.
[ME2]: Aerial Manipulator: Spraying conceptual design (supervisor: Professor Liu, collaborator: Mr. Shiqi GAO)
Achieving high-precision end-effector motion is a key challenge in aerial manipulation. This project explores the design and control of an aerial spraying platform that can generate dot-pattern coatings on vertical glass walls for bird-diverter applications, aiming to advance the precision of aerial manipulation in non-contact tasks. First, we will build up an aerial manipulator system that integrates a lightweight robotic arm with the existing multirotor, optimizing the system layout for balance, stiffness, and payload efficiency. Second, a compact spraying module will be developed and adapted as the end-effector to enable controlled droplet deposition at specified wall positions. Third, to ensure accurate performance near surfaces, we will design a control strategy that compensates for aerodynamic disturbances such as sidewall effects. The project involves mechanical design, CAD modeling, and ROS programming. Let’s make the campus bird-safe!
[ME3]: Aerial Manipulator: Sheet carrier conceptual design (supervisor: Professor Liu, collaborator: Mr. Shiqi GAO)
The ability to actively interact with the environment distinguishes aerial manipulators from conventional aircraft. This project aims to design an aerial manipulator capable of attaching dot-pattern sheets onto vertical glass walls as a novel bird-diverter solution. The work will involve three main components. First, we will establish an aerial manipulator system based on analyses of system balance and payload capacity. Second, a sheet-clicking mechanism will be developed to enable the end-effector to press and sweep across the sheet for firm and consistent attachment. Third, a hybrid force–motion control strategy will be designed to ensure smooth end-effector motion during contact while maintaining stable flight performance. The project emphasizes mechanical design, CAD modeling, and ROS-based programming, with the ultimate goal of contributing to a bird-friendly campus environment.
[ME4]: Sloshing Dynamic Modeling (supervisor: Professor Liu, collaborators: Keilan Pieper, Constantine Cheng)
The development of accurate models that effectively capture the sloshing dynamic modes in 3D axis has traditionally been broken down into a couple different models, specifically pendulum, mass spring dampener and port Hamiltonian methods. This project will be to use existing quadcopter drones to test how accurate dynamic models of a sloshing tank are to experimental counterparts. There are three main deliverables for this project, one, to use existing quadcopter systems with a variable length attached water tank and develop a testing algorithm to quantify difference in analytical sloshing models. The second will be an experimental test of how altering the length of slung load will affect the sloshing model accuracy and altering the size of the water tank. Does adding more length of a flexible rope alter the predicted dynamics. And finally recommendations for analytical models, how our existing models can be altered to be more accurate.
[ME5]: Quantifying Trust in Human Robot Interaction through Data Analysis and Simulation (supervisor: Professor Liu, collaborator: Darya Zanjanpour)
This project aims to measure and analyze human trust in autonomous systems by combining behavioral experiments, data analytics, and simulation-based modeling. Students will help design and conduct studies involving human participants interacting with semi-autonomous systems. The collected data, including task performance, response time, and self-reported trust, will be analyzed using Python. MATLAB will be used to improve existing simulations by integrating trust parameters that evaluate adaptive system behavior. The goal is to better understand how human trust changes during interaction and to create models that can predict and calibrate trust in real time. Strong programming skills in Python and MATLAB are required, and background knowledge in neuroscience or cognitive psychology would be an asset.
[ME6]: Data-driven Model Predictive Control of Quadrotors (supervisor: Professor Liu, collaborator: Dr. Kunwu Zhang)
Model Predictive Control (MPC) has proven to be an efficient tool for explicitly handling system constraints. However, traditional MPC strategies rely on accurate dynamic models to guarantee control performance. Alternatively, recent research efforts have sought to integrate data-driven methods with MPC to eliminate the dependency on accurate dynamic models for performance guarantee. This project aims to develop a data-driven MPC (DDPC) scheme for quadrotor flight control. There are three main objectives for this project. First, we will collect operational data from a quadrotor simulator in a ROS environment and establish a data-driven model using the Koopman operator. Second, we will deploy this model to develop a DDPC scheme for waypoint tracking tasks and verify its performance in the ROS environment. Finally, we will collect data from a quadrotor experimental platform to refine the data-driven model and conduct experimental testing of the proposed DDMPC approach.
To undergraduate students: Are you an undergraduate student looking to gain hands-on research experience or seeking a thesis project that makes a real impact? The FSC group routinely offers a number of research topics that are custom built for undergraduate students based on the group’s on-going research project needs. The students will actively work with the FSC graduate students to carry out research tasks.
Undergraduate (summer 2026, 4th-year thesis 2026-27) Research Topics
The following research topics are available for UofT’s Engineering Science for all three streams: Aerospace, Robotics, Machine Learning (or other engineering programs) students. The inquiry/application deadlines are: January 30th (for summer research internship) and June 30th (for 2025-26 4th-year thesis).
(no specific research topics is available at this time. We are recruiting 2 summer students, please check the FSC group’s research theme and recent research projects. If any of these topics is aligned with your interest, please specify in your application to Professor Liu. Please submit your application directly to Professor Liu by email with your CV, up-to-date transcripts, and a brief description of your research interests)
Interested students are encouraged to reach out early, as positions are limited and competitive.