David Busson

École nationale supérieure d'arts et métiers, ParisTech

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About

David Busson’s research focuses on the control and optimization of redundant robotic manipulators, particularly for tasks requiring high stiffness and force capacity during physical interaction with the environment. His major contributions include pioneering a task-oriented rigidity optimization method for 7-degree-of-freedom (DOF) redundant manipulators, enabling them to maintain maximal Cartesian stiffness during demanding operations like milling and drilling. This work, with 35 citations, provides a practical framework for selecting joint configurations that enhance end-effector rigidity without sacrificing redundancy. Busson also developed a pragmatic approach to exploiting the full force capacity of serial redundant manipulators, addressing the theoretical and practical challenges of maximizing force output while accounting for the robot’s own weight and dynamic constraints. His research, though early in its citation impact, offers valuable tools for industries requiring precise, high-force robotic interactions. Busson’s work stands out for its direct applicability to manufacturing and assembly tasks, bridging the gap between theoretical redundancy resolution and real-world stiffness and force requirements.