Projects

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.