Masoud Baghbahari

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About

Masoud Baghbahari’s research lies at the intersection of safe physical human–robot interaction (PHRI), tactile sensing, and real-time robotic control, with a strong emphasis on assistive technologies for users with disabilities. His most cited work, “A Passivity-Based Framework for Safe Physical Human–Robot Interaction” (2023, 4 citations), introduces a novel approach to ensuring compliant, stable contact between humans and assistive robots during activities of daily living—a critical step toward making robots safe and usable for vulnerable populations. Earlier contributions include “Automatic Grasping Using Tactile Sensing and Deep Calibration” (2019, 3 citations) and “Real-time policy generation and its application to robot grasping” (2018, 3 citations), where he tackled the challenge of enabling robots to adapt and act on immediate sensory data without relying on large, pre-trained datasets. By integrating passivity theory, tactile feedback, and real-time policy generation, Baghbahari’s work advances the practicality of autonomous grasping and human-safe robot interaction. His research is particularly notable for addressing the real-world constraints of assistive robotics, where safety, responsiveness, and minimal data requirements are paramount.