Max Robotics — Global Service Robot Directory + US Certification

About

Ohwon Kwon’s research bridges robotics, assistive technology, and deep learning to create intuitive systems that enhance human mobility and healthcare. His work centers on developing intelligent robotic platforms for patient transfer, prosthetic hand control, and remote medical imaging. Kwon’s most cited paper, “User Intention Based Intuitive Mobile Platform Control: Application to a Patient Transfer Robot” (2022, 13 citations), demonstrates his ability to translate user intent into seamless robotic assistance. He further advanced prosthetic technology in “Grasping Time and Pose Selection for Robotic Prosthetic Hand Control Using Deep Learning Based Object Detection” (2022, 9 citations), where deep learning enables automatic grasp selection—a critical step toward restoring dexterity for amputees. Kwon also made notable contributions to telemedicine, designing a robot-assisted tele-echography system (2017, 6 citations) that allows remote ultrasound imaging via a lightweight, handheld slave robot. He later validated its feasibility over 4G LTE mobile internet (2018, 4 citations), proving that reliable remote diagnosis is possible outside traditional clinical settings. With a growing citation record and a focus on real-world applications, Kwon’s work exemplifies how robotics and AI can directly improve quality of life—from safer patient handling to accessible medical imaging and smarter prosthetics.