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About

Kang-Won Lee is a pioneering researcher at the intersection of robotics, tactile sensing, and human-robot interaction, with a focus on enabling machines to perceive and manipulate the physical world through touch. His key contributions lie in developing vision-based force estimation methods that eliminate the need for traditional tactile or force sensors—a breakthrough for teleoperation and robotic grip control. His 2022 paper on vision-based interaction force estimation for robot grip motion has garnered 31 citations, while his 2021 work on high-sampling force estimation for teleoperation has been cited 17 times. More recently, Lee has advanced the concept of "robot synesthesia," integrating visuotactile feedback for dexterous in-hand manipulation (2024, 32 citations). He also introduced DexTouch, a multi-finger system that enables object manipulation purely through tactile sensing, and DeepTouch, which adapts touch interaction for underwater environments—both published in 2024 and 2022, respectively. Lee’s work is notable for pushing the boundaries of sensorless force estimation and multimodal perception, with direct applications in teleoperation, underwater robotics, and assistive technologies. His innovative approaches are shaping the future of autonomous manipulation in challenging environments.