Publications

For more detail check out our Google Scholar.

UAV See, UGV Do: Aerial Imagery and Virtual Teach Enabling Zero-Shot Ground Vehicle Repeat

D. Fisker, A. Krawciw, S. Lilge, M. Greeff, and T. D. Barfoot

IEEE International Conference on Intelligent Robots and Systems (IROS), 2025, Submitted.

Evaluation of Flight Parameters in UAV-based 3D Reconstruction for Rooftop Infrastructure Assessment

N. Chodura, M. Greeff, J. Woods

International Symposium on Automation and Robotics in Construction (ISARC), 2025, Accepted.

Bistable SMA-driven Engine for Pulse-jet Locomotion in Soft Aquatic Robots

G. Bedenik, A. Morales, S. Pieris, B. da Silva, J. W. Kurelek, M. Greeff, M. Robertson

IEEE RoboSoft, 2025, Accepted.

A Time and Place to Land: Online Learning-Based Distributed MPC for Multirotor Landing on Surface Vessel in Waves

J. Stephenson, W. S. Stewart, and M. Greeff

IEEE International Conference on Unmanned Aircraft Systems, 2025, Accepted.

Distributed Model Predictive Control for Cooperative Multirotor Landing on Uncrewed Surface Vessel in Waves

J. Stephenson, N. T. Duncan, and M. Greeff

IEEE International Conference on Unmanned Aircraft Systems, 2024

A Computationally Efficient Learning-Based Model Predictive Control for Multirotors under Aerodynamic Disturbances

B. Akbari and M. Greeff

IEEE International Conference on Unmanned Aircraft Systems, 2024

safe-control-gym: A Unified Benchmark Suite for Safe Learning-Based Control and Reinforcement Learning in Robotics

Z. Yuan, A. W. Hall, S. Zhou, L. Brunke, M. Greeff, J. Panerati, and A. P. Schoellig

IEEE Robotics and Automation Letters, 2022

Fly out the window: exploiting discrete-time flatness for fast vision-based multirotor flight

M. Greeff, S. Zhou, and A. P. Schoellig

IEEE Robotics and Automation Letters, 2022

Safe learning in robotics: from learning-based control to safe reinforcement learning

L. Brunke, M. Greeff, A. W. Hall, Z. Yuan, S. Zhou, J. Panerati, and A. P. Schoellig

Annual Review of Control, Robotics, and Autonomous Systems, vol. 5, iss. 1, 2022.

Exploiting differential flatness for robust learning-based tracking control using Gaussian processes

M. Greeff and A. P. Schoellig

IEEE Control Systems Letters, vol. 5, iss. 4, pp. 1121–1126, 2021.

Learning a stability filter for uncertain differentially flat systems using Gaussian processes

M. Greeff, A. W. Hall, and A. P. Schoellig

Proc. of the IEEE Conference on Decision and Control (CDC), 2021, pp. 789-794.

A perception-aware flatness-based model predictive controller for fast vision-based multirotor flight

M. Greeff, T. D. Barfoot, and A. P. Schoellig

Proc. of the International Federation of Automatic Control (IFAC) World Congress, 2020, p. 9412–9419.

There’s no place like home: visual teach and repeat for emergency return of multirotor UAVs during GPS failure

M. Warren, M. Greeff, B. Patel, J. Collier, A. P. Schoellig, and T. D. Barfoot

IEEE Robotics and Automation Letters, vol. 4, iss. 1, p. 161–168, 2019.

Flatness-based model predictive control for quadrotor trajectory tracking

M. Greeff and A. P. Schoellig

Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, p. 6740–6745.

Robora
Social Media

© Robora Lab. Queen's University Canada. Department of Electrical and Computer Engineering