Lucia Angelini

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About

Lucia Angelini is a leading researcher in the field of bimanual teleoperation and prosthetic control, with a focus on advancing human-robot interaction. Her work centers on developing intuitive, closed-loop systems that enhance the dexterity and safety of robotic platforms, particularly for applications in assistive technology and rehabilitation. A key contribution is the development of **LimbMATE**, a versatile platform for closed-loop research in prosthetics, which integrates machine learning for myoelectric pattern recognition to enable more natural, multi-functional control of robotic hands. This work addresses the growing demand for sophisticated control interfaces in modern prosthetics. Angelini also made significant strides in bimanual teleoperation with her revised **CollisionIK** algorithm, which solves the critical challenge of self-collision avoidance in dual-arm systems without introducing performance delays. Despite being early in her career, her publications have already garnered attention, with each cited paper accumulating 2 citations, signaling a promising trajectory. Her innovative approaches to collision avoidance and prosthetic control position her as a rising figure in robotics, with potential to transform how humans interact with complex robotic systems in both clinical and industrial settings.