3 papers
cs.RO2025
Learning thin deformable object manipulation with a multi-sensory integrated soft hand
Chao Zhao, Chunli Jiang, Lifan Luo +3
Robotic manipulation has made significant advancements, with systems demonstrating high precision and repeatability. However, this remarkable precision often fails to translate int…
cs.RO2025
Master Rules from Chaos: Learning to Reason, Plan, and Interact from Chaos for Tangram Assembly
Chao Zhao, Chunli Jiang, Lifan Luo +4
Tangram assembly, the art of human intelligence and manipulation dexterity, is a new challenge for robotics and reveals the limitations of state-of-the-arts. Here, we describe our…
cs.RO2025
Generative Artificial Intelligence in Robotic Manipulation: A Survey
Kun Zhang, Peng Yun, Jun Cen +11
This survey provides a comprehensive review on recent advancements of generative learning models in robotic manipulation, addressing key challenges in the field. Robotic manipulati…