Craig W. Bailey

Papers

Total Citations

H-Index

About

Craig W. Bailey has made foundational contributions to human-robot interaction and sketch-based interfaces, pioneering methods that allow people to communicate with machines through natural, hand-drawn gestures. His most influential work addresses the central challenge of robust symbol recognition in sketch-based systems. In his highly cited 2004 paper (44 citations), Bailey introduced Hidden Markov Models (HMMs) for temporal pattern recognition, overcoming artifacts like varying sketching styles and affine transformations—a breakthrough that made sketch interfaces more practical and reliable. He extended this work into robotics with another landmark 2004 paper (43 citations), where he developed a PDA-based sketching interface enabling users to direct mobile robots along hand-drawn navigation paths. This work demonstrated that imprecise, human-scale route sketches could be interpreted by robots, bridging the gap between natural human communication and autonomous machine control. Bailey’s research has been instrumental in advancing intuitive human-robot communication, influencing subsequent work in assistive robotics, mobile navigation, and sketch-based design tools. His contributions remain highly cited for their practical impact on making robotic systems more accessible to non-expert users.