James Richard Forbes
McGill University, University of Michigan–Ann Arbor, University of Toronto, Polytechnique Montréal
Papers
33
Total Citations
417
H-Index
13
About
James Richard Forbes is a prominent robotics and control systems researcher whose work spans multi-agent localization, flexible robotic systems, and state estimation. His research has made substantial contributions to the challenge of cooperative robotics in GPS-denied environments, most notably through his highly cited 2021 paper on attitude-coupled range measurements for relative position estimation (60 citations), which leverages affordable ultra-wideband radio technology to enable accurate inter-agent localization. Forbes has also advanced the modeling and control of complex mechanical systems, including spherical robots, cable-driven parallel robots, and flexible-joint manipulators, demonstrating a breadth that bridges theoretical rigor with practical application. His foundational work on gain-scheduled strictly positive real controllers and passivity-based methods for flexible robotic systems, developed across multiple publications from 2010 onward, has provided engineers with robust frameworks for motion control. Forbes has further contributed to nonlinear state estimation under inequality constraints and to solving classical attitude estimation problems such as Wahba's problem on SO(n). More recently, his work on ultra-wideband calibration and optimal multi-robot formation design underscores his continued relevance in emerging autonomous systems research, cementing his reputation as a versatile and impactful figure in modern robotics and estimation theory.
Research Focus
Key Achievements
Top Papers
- 1
- 2Modeling of spherical robots rolling on generic surfaces38 citations · 2014
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- 5Saturated proportional derivative control of flexible-joint manipulators22 citations · 2014
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- 9On the Solution ofWahba’s Problem on S O (n)17 citations · 2013
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