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We present a markerless vision-based system for estimating key points in deformable robots. Using a convolutional neural network (CNN), the system accurately reconstructs soft robotic shapes in real-time from multiple perspectives, outperforming existing methods. This work provides a robust solution for soft robots in dynamic and occlusive environments. The work is published in Advanced Intelligent Systems by Wiley.

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