91滴滴

Updated: Sun, 10/06/2024 - 10:30

From Saturday, Oct. 5 through Monday, Oct. 7, the Downtown and Macdonald Campuses will be open only to 91滴滴 students, employees and essential visitors. Many classes will be held online. Remote work required where possible. See Campus Public Safety website for details.

Du samedi 5 octobre au lundi 7 octobre, le campus du centre-ville et le campus Macdonald ne seront accessibles qu鈥檃ux 茅tudiants et aux membres du personnel de l鈥橴niversit茅 91滴滴, ainsi qu鈥檃ux visiteurs essentiels. De nombreux cours auront lieu en ligne. Le personnel devra travailler 脿 distance, si possible. Voir le site Web de la Direction de la protection et de la pr茅vention pour plus de d茅tails.

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James Forbes

Title: 
Associate Professor
Academic title(s): 

William Dawson Scholar

James Forbes
Contact Information
Address: 

Macdonald Engineering Building, Room 158

Email address: 
james.richard.forbes [at] mcgill.ca
Degree(s): 

Ph.D. Aerospace Science and Engineering, University of Toronto
M.A.Sc. Aerospace Science and Engineering, University of Toronto
B.A.Sc. Mechanical Engineering, University of Waterloo

Courses: 

MECH 309: Numerical Methods in Mechanical Engineering (3 credits)
MECH 412: System Dynamics and Control (3 Credits)
MECH 513: Control Systems (3 Credits)
MECH 672: Navigation and Control of Robotic and Aerospace Systems (4 credits)

Research areas: 
Dynamics and Control
Selected publications: 
  • T. Hitchcox and J. R. Forbes, 鈥淢ind the Gap: Norm-Aware Adaptive Robust Loss for Multivariate Least-Squares Problems,鈥� IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7116鈥�7123, 2022.
  • F. Ahmed, L. A. Sobiesiak, and J. R. Forbes,鈥淢odel Predictive Control of a Tandem-Rotor Helicopter with a Non-Uniformly Spaced Prediction Horizon,鈥� IEEE Control Systems Letters, vol. 6, pp. 2828鈥� 2833, 2022.
  • K. Lee and J. R. Forbes, 鈥淧osition and Attitude Tracking Control Using CCW and SNI System Theory With Applications to Multi-agent Systems,鈥� Automatica, vol. 139, p. 110203, 2022.
  • T. D. Barfoot, J. R. Forbes, and G. M. D鈥橢leuterio, 鈥淰ectorial Parameterizations of Pose,鈥� Robotica, vol. 40, no. 7, pp. 2409鈥�2427, 2022.
  • Z. C. Gau, V. Korotkine, J. R. Forbes, and T. D. Barfoot, 鈥淜oopman Linearization for Data-Driven Batch State Estimation of Control-Affine Systems,鈥� IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 866鈥�873, 2022.
  • D. Lisus, C. C. Cossette, M. Shalaby, and J. R. Forbes, 鈥淗eading Estimation Using Ultra-wideband Received Signal Strength and Gaussian Processes,鈥� IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8387鈥�8393, 2021.
  • M. Shalaby, C. C. Cossette, J. R. Forbes, and J. Le Ny, 鈥淩elative Position Estimation in Multi- Agent Systems Using Attitude-Coupled Range Measurements,鈥� IEEE Robotics and Automation Let- ters, vol. 6, no. 3, pp. 4955鈥�4961, 2021.
  • M. Cohen, K. Abdulrahim, and J. R. Forbes, 鈥淔inite-Horizon LQR Control of Quadrotors on SE_2(3),鈥� IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5748鈥�5755, 2020.
  • N. van der Laan, M. Cohen, J. Arsenault, and J. R. Forbes, 鈥淭he Invariant Rauch-Tung-Striebel Smoother,鈥� IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5067鈥�5074, 2020.
  • T. D. Barfoot, J. R. Forbes, and D. Yoon, 鈥淓xactly Sparse Gaussian Variational Inference with Ap- plication to Derivative-Free Batch Nonlinear State Estimation,鈥� International Journal of Robotics Research, vol. 39, no. 13, pp. 1473鈥�1502, 2020.
  • C. C. Cossette, A. Walsh, and J. R. Forbes, 鈥淭he Complex-Step Derivative Approximation on Matrix Lie Groups," IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 906-913, 2020.
  • D. E. Zlotnik and J. R. Forbes, 鈥淗igher-Order Nonlinear Complementary Filtering on Lie Groups,鈥� IEEE Transactions on Automatic Control, vol. 64, no. 5, pp. 1772鈥�1783, 2019.
  • D. E. Zlotnik and J. R. Forbes, 鈥淕radient-Based Observer for Simultaneous Localization and Mapping,鈥� IEEE Transactions on Automatic Control, vol. 63, no. 12, pp. 4338 鈥� 4344, 2018.

听

Current research: 

Navigation, Guidance, and Control

  • Nonlinear state estimation including batch and filtering methods for robot navigation
  • Nonlinear control including Lyapunov approaches, input-output stability, and gain-scheduled control
  • Controller synthesis via numerical optimization and Linear Matrix Inequalities (LMIs)
  • Data-driven modelling and system identification
  • The application of mathematics, numerical optimization, and machine learning tools to problems found in robotics
    听

Robotics Applications

  • Unmanned Aerial Vehicles (UAVs)
  • Unmanned Ground Vehicles (UGVs), including on- and off-road vehicles, rail vehicles
  • Autonomous Underwater Vehicles (AUV)
  • SLAM
  • Serial robots
  • Cable-actuated robots
Areas of interest: 

Primary Research Theme: Dynamics and Control

Research Lab/Group:听

I am interested in navigation, guidance, and control (commonly referred to as 鈥淕NC鈥�) techniques for robotic systems. I am interested in fundamental theoretical developments, as well as the application of new and existing theories to practical, real-world problems.

听

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