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cs.RO2025
Prompt-responsive Object Retrieval with Memory-augmented Student-Teacher Learning
Malte Mosbach, Sven Behnke
Building models responsive to input prompts represents a transformative shift in machine learning. This paradigm holds significant potential for robotics problems, such as targeted…
cs.RO2024
Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects
Malte Mosbach, Sven Behnke
Interactive grasping from clutter, akin to human dexterity, is one of the longest-standing problems in robot learning. Challenges stem from the intricacies of visual perception, th…