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Found 4 papers, 1 papers with code
ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics
Robotic manipulation in everyday scenarios, especially in unstructured environments, requires skills in pose-aware object manipulation (POM), which adapts robots' grasping and handling according to an object's 6D pose.
BeTAIL: Behavior Transformer Adversarial Imitation Learning from Human Racing Gameplay
Thus, we propose BeTAIL: Behavior Transformer Adversarial Imitation Learning, which combines a Behavior Transformer (BeT) policy from human demonstrations with online AIL.
GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects
Results show that GAMMA significantly outperforms SOTA articulation modeling and manipulation algorithms in unseen and cross-category articulated objects.
Skill-Critic: Refining Learned Skills for Reinforcement Learning
Hierarchical reinforcement learning (RL) can accelerate long-horizon decision-making by temporally abstracting a policy into multiple levels.
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