Projects are often done in collaboration with an industry sponsor and supported by NSERC, FRQNT, or Mitacs. Support of both industry partners and government funding agencies is graciously acknowledged.

For a list of publications related to these projects, see google scholar.

Current Projects

  • Invariant State Estimation Methods

Extension and application of the invariant extended Kalman filter on matrix Lie groups. For example, invariant forms of batch estimation, SLAM, monocular-IMU navigation, and others.
  • Autonomous Underwater Vehicle (AUV) Navigation

Using a laser scanner, DVL, and IMU, ascertain the position of an AUV, as well as map the surrounding underwater environment.
  • Industrial Robot Control

Design of high-performance control architectures for ultra-compact industrial robot arms. Reduce gearbox-induced vibration as well as increase frequency of pick-and-place operations.
  • Koopman-operator-based Nonlinear System Identification

Koopman operator theory for data driven modelling and control for nonlinear systems.
  • Navigation and Control of Robotic Networks using UWB Signals

Research and development of state-estimation and formation control algorithms for groups of robots using UWB signals for localization. In collaboration with the Mobile Robotics and Autonomous Systems Laboratory, École Polytechnique, Montréal.
  • Dynamic SLAM for Ground Vehicles

Stereo SLAM as well as dynamic object tracking for ground vehicles in invariant framework.
  • Linear System Identification of Viscoelastic Tissue

Building models for haptic feedback and control in spinal interbody fusion surgical simulations.
  • State Estimation using Thermal Imaging

Homography estimation and robot navigation using thermal cameras.

Past Projects

  • Constrained Filtering in Rail Environments

When GPS data is poor or unavailable, estimate a train's position using an IMU only. Specifically, exploit the fact the train is constrained to a railway track with unique features (e.g., unique curvature, grade, etc.)
  • Control of Industrial Crane Systems

Research and implementation of fully autonomous feedback control strategies for industrial crane systems.
  • LIDAR-Inertial-Visual Navigation

Develop a tightly-coupled Visual-Inertial-LIDAR simultaneous localization and mapping (SLAM) algorithm for unmanned aerial vehicle (UAV) partnership with ARA Robotique.
  • Control of Nonlinear, Viscoelastic Tissues

Develop a system that can test mechanical and contractile functionality of human or animal muscle tissues while exposed to drugs, biological mediators, and/or environmental factors.
  • DReCon: Data-Driven Responsive Control of Physics-Based Characters

An reinforcement-learning (RL) based method of controlling physically simulated humanoids that learns from unstructured motion-capture, emphasizing responsiveness to user input, quality, and low runtime cost for application in video-games.
  • Unconventional Unmanned Aerial Vehicle (UAV) NGC

Research on navigation, guidance, and control (NGC) of unconventional VTOL UAVs, focus on real-time estimation of wind velocity using standard sensors onboard a UAV. Use of machine learning techniques.
  • Guidance and Nonlinear Control of Multicoptors

Guidance and control of multicopter landing using MPC on matrix Lie group.