Max Robotics — Global Service Robot Directory + US Certification

About

Sina Parastegari’s research lies at the critical intersection of human-robot interaction, manipulation, and grasp taxonomy, with a central focus on making robot-to-human object handovers safe, intuitive, and failure-resistant. His most influential work, “Modeling human reaching phase in human-human object handover” (44 citations), established foundational models for selecting safe and comfortable object transfer configurations, directly informing robot trajectory planning. Parastegari further advanced this domain by developing fail-safe controllers that use object acceleration as a key sensory cue to prevent drops, and by systematically analyzing failure recovery strategies to reduce handover error rates—work that has garnered over 20 citations each. Beyond handovers, he contributed a novel grasp taxonomy based on force distribution patterns (22 citations), derived from human studies, which provides a data-driven framework for programming assistive robots by demonstration. His kinematic modeling of wheeled-tip manipulation systems (7 citations) also expanded the theoretical toolkit for dexterous object manipulation. Collectively, Parastegari’s work has shaped how robots physically interact with humans, emphasizing comfort, safety, and robustness—core requirements for assistive robotics in daily living.