Poya Khalaf
Papers
4
Total Citations
50
H-Index
4
About
Poya Khalaf’s research lies at the intersection of energy-efficient robotics, regenerative drive systems, and human-centered prosthesis design. His most impactful work focuses on parametric optimization of stored energy in robots with regenerative drives, where he formulated and solved the problem of maximizing energy storage through physical design parameters—a critical step toward sustainable, self-powered robotic systems. In his 2016 paper (16 citations), he introduced a framework for optimizing energy in robots with semi-active and fully-active joints, while his 2017 follow-up (15 citations) provided global, closed-form solutions for serial robots with energy regeneration, enabling practical implementation. Khalaf also made notable contributions to assistive robotics, developing multi-objective optimization methods for a prosthesis test robot (13 citations) to achieve human-like walking through impedance parameter tuning. His 2019 work (6 citations) extended this with fuzzy real-time optimization, enhancing adaptability. With a clear focus on marrying theoretical optimization with real-world robotic applications, Khalaf’s work has advanced both energy autonomy in robotics and the fidelity of prosthetic testing platforms, offering foundational tools for researchers in mechatronics and rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
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