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About

Roger Boudreau’s research centers on the kinematics, dynamics, and control of robotic manipulators, with a particular focus on parallel mechanisms and trajectory optimization. His major contributions include developing a length-optimized smooth obstacle avoidance algorithm for robotic manipulators, which uses a 3-4-5 interpolating polynomial to generate collision-free joint-space trajectories, and pioneering methods to compute the available wrench and force sets of kinematically redundant planar parallel manipulators, such as the 3-RPRR design. These latter works, each cited four times, provide exact, computationally efficient algorithms validated against brute-force approaches, significantly advancing the analysis of redundant parallel robots. Boudreau’s impact is further demonstrated by his early work applying time series and polynomial learning networks to robot trajectory error control, which laid groundwork for adaptive control strategies. His research bridges theoretical kinematics with practical control solutions, offering tools that reduce computational time while maintaining precision—a valuable contribution for students and engineers designing agile, redundant robotic systems.