Lance McCann

Papers

Total Citations

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About

Lance McCann is a pioneering researcher at the intersection of robotics, manufacturing, and data-driven control systems. His work focuses on enabling robots to safely and precisely interact with elastic, deformable workpieces—a critical challenge in modern manufacturing processes like clamping and drilling. McCann’s major contribution lies in developing active, data-enabled learning frameworks that allow robots to adapt to the unpredictable behavior of flexible materials in real time. By integrating machine learning with control theory, his methods reduce reliance on complex physical models, instead leveraging sensor data to maintain tool-workpiece normality and minimize damaging shear forces. Though his most-cited papers, including "Active Data-Enabled Robot Learning of Elastic Workpiece Interactions" (2024) and "Data-Based Learning for Control of Elastic Interactions Between Robot and Workpiece" (2019), each hold 2 citations, their impact is growing as the field recognizes the importance of adaptive robotic manipulation. McCann’s work is foundational for advancing automation in industries requiring high-precision handling of compliant materials, promising safer, more efficient manufacturing systems.