苹果淫院

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James Richard Forbes

James Richard Forbes
Contact Information
Email address: 
james.richard.forbes [at] mcgill.ca
Group: 
Full Member
Department: 
Mechanical Engineering
Area(s): 
Sustainable Industrial Processes & Manufacturing
Renewable Energy & Energy Efficiency
Sustainable Infrastructure & Urban Development
Current research: 

James Richard Forbes received the听. degree in Mechanical Engineering (Honours, Co-op) from the University of Waterloo, Waterloo, ON, Canada, and the听. and Ph.D. degrees in Aerospace Science and Engineering from the University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, ON, Canada, in 2008 and 2011, respectively. James is currently Associate Professor of Mechanical Engineering at 苹果淫院, Montreal, QC, Canada. In recognition of his research contributions James was awarded a William Dawson Scholar award in 2018 for a 5 year term, which was renewed in 2023 for another 5 year term. James is a Full Member of the Centre for Intelligent Machines (CIM) and a Member of the Group for Research in Decision Analysis (GERAD). James was awarded the 苹果淫院 Associate for Mechanical Engineering (MAME) Professor of the Year Award in 2016, the Engineering Class of 1944 Outstanding Teaching Award in 2018, and the Carrie M. Derick Award for Graduate Supervision and Teaching in 2020. James is currently an associate editor of the Int. Journal of Robotics Research.听James' research group, the Dynamics, Estimation, and Control in Aerospace and Robotics (DECAR) group, conducts fundamental and applied research in collaboration with various industrial companies in Quebec, Canada, and internationally. As a member of TISED, James is interested in leveraging control, optimization, and data-driven tools to enhance statable technologies in collaboration with other TISED members and industry partners.

Areas of interest: 

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

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

7 SDG Affordable and clean energy9 SDG Industry, innovation, and infrastructure13 SDG Climate Action

Stream: 
SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation and Infrastructure
SDG 13 Climate Action
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