16 datasets found

The dataset used in the paper is a MuJoCo environment, with 13-states and 4-control inputs, nonlinear dynamics with polynomial dependency in the control inputs.

The HandManipulateBlock environment from OpenAI gym robotics suite

The FetchPickAndPlace and HandManipulateBlock environments from OpenAI gym robotics suite

The FetchPush, FetchPickAndPlace and HandManipulateBlock environments from OpenAI gym robotics suite

The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games.

The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games.

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 Continual World benchmark consists of ten realistic robotic manipulation tasks.

A benchmark for evaluating task compositionality and long-horizon tasks through object manipulation, with language serving as the mechanism for goal specification.

A dataset for robotic manipulation tasks, including ChestPush, ChestPickAndPlace, and BlockStack.

A dataset for multi-step sparse reward tasks, including gridworld tasks and robotic manipulation tasks.

The dataset used in the paper is a robotic manipulation task dataset, which consists of trajectories and preference labels.

The DeepMind Control Suite is a collection of 20 robotic manipulation tasks, each with 5 different environments and 5 different robot parameters. The tasks are designed to test...

The dataset used in the paper is the Gymnasium MuJoCo benchmark, which is a collection of robotic manipulation tasks.

The dataset used in the paper is the MuJoCo benchmark, which is a collection of robotic manipulation tasks.

The dataset used in the paper is a collection of simulated environments, including blockworld, canada, cart, cartpole, cartpoleBalance, cartpoleParallelDouble,...