Colm Higgins

Papers

Total Citations

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About

Colm Higgins is a researcher at the forefront of advanced manufacturing, specializing in the intersection of industrial robotics and precision machining. His work focuses on enhancing the accuracy and reliability of automated systems, particularly through the application of machine learning and advanced metrology. Higgins’s most cited paper, “Machine Learning Methods to Improve the Accuracy of Industrial Robots” (2023, 9 citations), addresses a critical bottleneck in aerospace manufacturing, demonstrating how AI can compensate for robotic inaccuracies to enable high-precision assembly tasks. He has also made significant contributions to the field of Parallel Kinematic Machines (PKMs), with his 2022 study on “Stiffness Measurement of Parallel Kinematic Machines Considering Gravity Effect” (3 citations) providing a novel framework for modeling stiffness—a key factor in machining quality—by accounting for gravitational deformation. His latest work (2025) extends this research to error compensation strategies for the Exechon X-mini PKM, further bridging the gap between flexible robotics and the rigidity of traditional CNC machines. With a growing citation record and a clear trajectory toward solving real-world industrial challenges, Higgins is establishing himself as a key voice in the future of smart, adaptive manufacturing systems.