A collaborative research effort involving Carnegie Mellon University, Meta FAIR, the University of California, Berkeley, the Technical University of Dresden in Germany, and the Centre for Tactile Internet with Human-in-the-Loop (CeTI) has led to the development of NeuralFeels, an innovative machine learning model. This model enhances robotic perception by integrating vision and touch sensing capabilities within a robotic hand, enabling it to reconstruct and track objects that are not directly visible. The initiative aims to advance the field of robotics by improving how machines interact with and understand their environments, addressing limitations of traditional sensing methods. The research findings were recently announced, showcasing the potential of NeuralFeels to redefine the capabilities of robotic systems in various applications.
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