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About

M. Manivannan is a leading researcher in haptics and tactile sensing, with a focus on medical simulation and bio-inspired robotics. His work bridges the gap between human touch perception and engineered systems, particularly in needle insertion training—a critical skill for physicians and paramedics. His most cited paper, "Haptic Feedback in Needle Insertion Modeling and Simulation" (2017, 46 citations), addresses the need for realistic haptic cues to improve patient safety during procedures. Manivannan has also pioneered novel tactile sensors for robotics, including a high-sensitive flexible capacitive force sensor using PDMS (2023) and whisker-inspired sensors modeled after rodent and pinniped tactile systems. His "Visibility-Inspired Models of Touch Sensors for Navigation" (2022) offers a theoretical framework akin to the pinhole camera model, providing idealized characterizations for mobile robot navigation. More recently, his "Subblescope" (2024) introduces a soft, affordable vision-based tactile sensor using a single air bubble, advancing haptic feedback in robotic fingers. With a portfolio spanning medical training, flexible electronics, and bio-inspired navigation, Manivannan’s work demonstrates significant impact in enhancing both human and robotic tactile capabilities.