Caitlin Reyda

Papers

Total Citations

204

H-Index

About

Caitlin Reyda is a pioneering researcher in the field of tactile robotics and haptic perception, whose work bridges the gap between sensor-based touch and machine intelligence. Her primary research areas include tactile object recognition, haptic exploration strategies, and sensorimotor perception for robotic systems. Reyda's major contributions center on developing methods that enable robots to identify and understand objects through touch alone, fundamentally advancing how machines interact with the physical world. Her landmark 2011 paper, "Tactile-Object Recognition From Appearance Information," which has garnered 144 citations, introduced a novel framework that combines object recognition from tactile appearance with purposeful haptic exploration—a dual approach that revolutionized how robots extract meaningful information from unknown objects. In her equally influential work, "Object mapping, recognition, and localization from tactile geometry" (60 citations), Reyda pioneered the use of tactile sensors as imaging devices, creating mosaic-based object representations that allow for robust recognition and localization. Her innovative algorithms for tactile geometry mapping have laid crucial groundwork for applications in prosthetics, manufacturing, and autonomous systems. Reyda's research continues to inspire new generations of roboticists, demonstrating that touch—often overlooked in favor of vision—is an equally rich and essential modality for intelligent machine perception.