Daniel Zimmer

SGFAM: Semantic and Geometric Features Aggregation for Dense Shape Matching in Generalizable Robotic Manipulation

To automate processes like polishing or cleaning at scale, robots must be able to adapt learned skills to new object instances without manual reprogramming. Applications requiring tool-surface interactions face a significant challenge in transferring manipulation strategies to novel objects due to s