11 datasets found

OLAF is a learning system that allows everyday users to teach a robot using verbal corrections when the robot makes mistakes.

The RLBench dataset is used for robot learning benchmark and learning environment.

Open X-Embodiment: Robotic learning datasets and RT-X models

Aligning robot behavior with human preferences is crucial for deploying embodied AI agents in human-centered environments. A promising solution is interactive imitation learning...

The dataset used in the paper is RLBench, a standard benchmark for vision-based robotics which has been shown to serve as a proxy for real-robot experiments.

The Realworld Kitchen dataset contains four sub-tasks, namely, opening the oven, grasping a cloth, closing a drawer, and turning on a light.

The Franka Kitchen environment is a challenging long-range control problem, which involves a simulated 9-DOF Franka Emika Robot in a kitchen setting.

Human demonstration videos are a widely available data source for robot learning and an intuitive user interface for expressing desired behavior.

The YCB object and model set is a benchmark for manipulation research, consisting of 15 object categories and 3D models.

PartNet Mobility and GAPart-Net are datasets of articulated objects with their part configurations.

Gen2Sim generates 3D assets from object-centric images using image diffusion models and predicts physical parameters for them using LLMs.