Arya Shabani

Institut de Robòtica i Informàtica Industrial, University of Tehran, University of Bath, Universitat Politècnica de Catalunya

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About

Arya Shabani’s research bridges the foundational mathematics of robotics with practical human-robot interaction, making significant contributions across kinematics, rehabilitation, and collaborative manufacturing. A central thread in Shabani’s work is solving complex geometric and kinematic problems. Their most cited paper (43 citations) provides closed-form formulas for the 3-D nearest rotation matrix problem, a critical challenge in robotics, computer graphics, and computer vision for restoring orthonormality from noisy data. This work offers a computationally elegant alternative to the standard singular value decomposition approach. Shabani further advanced kinematic theory by developing a branch-and-prune method for solving closure equations using dual quaternions (7 citations), simplifying the solution of complex loop equations. Beyond theory, Shabani has made impactful contributions to human-centered robotics. They developed a bio-signal interface for a knee rehabilitation robot that uses EMG signals from thigh muscles (13 citations), enabling active and passive exercises driven by patient intent. More recently, Shabani proposed a multimodal sensor framework for human-robot collaboration in assembly tasks (10 citations), integrating vision for user identification and gesture recognition to enable seamless, safe teamwork. This blend of rigorous mathematical foundations and applied, human-aware systems defines Shabani’s distinctive and valuable research profile.