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cs.RO2024
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
cs.RO2024★ 2 cited
3D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensing
Binghao Huang, Yixuan Wang, Xinyi Yang +2
Tactile and visual perception are both crucial for humans to perform fine-grained interactions with their environment. Developing similar multi-modal sensing capabilities for robot…
cs.RO2024
RoboPack: Learning Tactile-Informed Dynamics Models for Dense Packing
Bo Ai, Stephen Tian, Haochen Shi +4
Tactile feedback is critical for understanding the dynamics of both rigid and deformable objects in many manipulation tasks, such as non-prehensile manipulation and dense packing.…