Alina Ninett Panfir

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About

Alina Ninett Panfir is a robotics researcher whose work focuses on humanoid robot collaboration, imitation learning, and intelligent task planning for multi-robot systems. Her research addresses the challenge of enabling robots to work together autonomously, particularly when individual robots cannot complete complex operations alone. In her most-cited paper (7 citations), she proposed a novel method for collaboration between two NAO robots to jointly manipulate objects, advancing the field of cooperative robotics. She also explored how humanoid robots can learn new skills through imitation, leveraging their human-like form to adapt to dynamic workspaces. Panfir further contributed to the development of control interfaces using LabView for collaborative systems, streamlining data acquisition and motor control. Her work on intelligent task planning for industrial mobile robots integrates model-based and case-based reasoning to support end goals in multi-robot environments. With a total of 19 citations across her key publications, Panfir’s research provides foundational insights into robot teamwork, skill acquisition, and autonomous planning—areas critical to the future of human-robot collaboration and industrial automation.