Patrick Keenan

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About

Patrick Keenan’s research sits at the intersection of robotic manipulation, visual servoing, and medical robotics, with a focus on enabling precise autonomous interaction with challenging surfaces. His most influential work, a 2018 study on a hybrid vision-based surface coverage method for robotic inspection (14 citations), established a framework for reliably scanning complex geometries. Keenan made a significant contribution to medical robotics through his 2017 paper on backlash characterization and position control of a robotic catheter manipulator (12 citations), where he developed an experimentally-based kinematic model to enhance the precision of minimally invasive surgical tools. His most conceptually novel contribution is his 2020 investigation into vision-based robotic traversal of textureless smooth surfaces (7 citations). In this work, Keenan proposed a novel 6-degree-of-freedom visual servoing formulation that leverages a surface’s local differential properties, enabling a robot to maintain tool positioning relative to a featureless workpiece—a critical capability for automated inspection and manufacturing. Collectively, his work demonstrates a sustained effort to solve fundamental perception and control problems for robots operating in unstructured or visually ambiguous environments, with clear translational potential for both industrial automation and surgical assistance.