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Daniel Bargmann

2 accepted papers

2024

Enabling Maintainablity of Robot Programs in Assembly by Extracting Compositions of Force- and Position-Based Robot Skills from Learning-from-Demonstration Models

IROS 2024poster

To this day, only a small number of industrial robots is used in assembly. One key reason for this is that specific contact situations require the introduction of force-control schemes. The parameters for those schemes are hard to select in practice, because they require in-depth expertise about the…

Cited by 1SourceScholar
2023

Flexible Gear Assembly with Visual Servoing and Force Feedback

IROS 2023poster

This paper presents a vision-guided two-stage approach with force feedback to achieve high-precision and flexible gear assembly. The proposed approach integrates YOLO to coarsely localize the target workpiece in a searching phase and deep reinforcement learning (DRL) to complete the insertion. Speci…

Cited by 5SourceScholar