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This paper presents a framework for modeling tendon driven continuum robots (TDCRs) using action conditioned point flow matching to predict their 3D geometry from motor actuation states. The authors developed a lightweight 3D printed TDCR platform and a data collection pipeline that utilizes RGB-D cameras to gather point cloud data for training the model. Experimental results demonstrate improved shape prediction accuracy compared to existing methods, highlighting the effectiveness of the proposed data-driv

Author

emmawithsai

Language

EN