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Found 5 papers, 4 papers with code
SliceIt! -- A Dual Simulator Framework for Learning Robot Food Slicing
Our approach involves using Reinforcement Learning (RL) to train a robot to compliantly manipulate a knife, by reducing the contact forces exerted by the food items and by the cutting board.
Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist
This study tackles the representative yet challenging contact-rich peg-in-hole task of robotic assembly, using a soft wrist that can operate more safely and tolerate lower-frequency control signals than a rigid one.
Vision-Language Interpreter for Robot Task Planning
By generating PDs from language instruction and scene observation, we can drive symbolic planners in a language-guided framework.
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning Study
The Reinforcement Learning (RL) paradigm has been an essential tool for automating robotic tasks.
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep Reinforcement Learning Approach
Industrial robot manipulators are playing a more significant role in modern manufacturing industries.
