Papers
13
Total Citations
282
H-Index
9
About
Erfan Shahriari’s research lies at the intersection of robot control, human-robot interaction, and rehabilitation robotics, with a core focus on passivity-based control and energy-aware frameworks. His most influential contribution is the development of virtual energy tanks—a paradigm that ensures stable, safe interactions by regulating power flow between robots and their environments. In his highly cited 2017 work (46 citations), Shahriari introduced a method for adapting dynamic movement primitives to contact forces, enabling robots to learn from demonstrations while maintaining passivity. He later extended this with valve-based energy tanks (2018, 31 citations), which allow controllers to embed multiple objectives without sacrificing stability. His unified force-impedance control (2024, 36 citations) integrates compliance and exact force regulation, a long-standing challenge in manipulation. Shahriari’s work on multi-manual object manipulation (2022, 32 citations) and patient-aware rehabilitation (2019) demonstrates the practical impact of his theories—enabling teams of robots to coordinate safely and adapting therapy based on patient participation. With over 260 citations across his top papers, Shahriari has established himself as a leading voice in making robots both robust and responsive in physical collaboration.
Research Focus
Key Achievements
Top Papers
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- 3Unified force-impedance control36 citations · 2024
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- 7Energy-based Adaptive Control and Learning for Patient-Aware Rehabilitation13 citations · 2019
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