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Found 7 papers, 3 papers with code
Evaluating Real-World Robot Manipulation Policies in Simulation
We then employ these approaches to create SIMPLER, a collection of simulated environments for manipulation policy evaluation on common real robot setups.
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Generalization remains one of the most important desiderata for robust robot learning systems.
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Our goal is to enable a single end-to-end trained model to both learn to map robot observations to actions and enjoy the benefits of large-scale pretraining on language and vision-language data from the web.
Language to Rewards for Robotic Skill Synthesis
However, since low-level robot actions are hardware-dependent and underrepresented in LLM training corpora, existing efforts in applying LLMs to robotics have largely treated LLMs as semantic planners or relied on human-engineered control primitives to interface with the robot.
Jump-Start Reinforcement Learning
In addition, we provide an upper bound on the sample complexity of JSRL and show that with the help of a guide-policy, one can improve the sample complexity for non-optimism exploration methods from exponential in horizon to polynomial.
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
We show how low-level skills can be combined with large language models so that the language model provides high-level knowledge about the procedures for performing complex and temporally-extended instructions, while value functions associated with these skills provide the grounding necessary to connect this knowledge to a particular physical environment.
COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing
General contact-rich manipulation problems are long-standing challenges in robotics due to the difficulty of understanding complicated contact physics.
