79 datasets found

Groups: Reinforcement Learning Organizations: No Organization

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  • Giraffe

    The dataset used in the paper is a collection of images of objects in 3D space, with multiple views of each object.

  • Nerf++

    The dataset used in the paper is a collection of images of objects in 3D space, with multiple views of each object.

  • NeRF-RL

    The dataset used in the paper is a collection of images of objects in 3D space, with multiple views of each object.

  • Robomimic Environment

    Robomimic environment consists of tasks such as lift, can, square, tool-hang, and transport.

  • D4RL Benchmark Suite

    D4RL benchmark suite consists of tasks such as locomotion, antmaze, adroit, and kitchen.

  • Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning

    Offline reinforcement learning (RL) paradigm provides a general recipe to convert static behavior datasets into policies that can perform better than the policy that collected...

  • RL-VLM-AR

    The dataset used in the paper is a set of real-world robot learning tasks, including Create-Reacher, UR5-VisualReacher, Vector-ChargerDetector, and Franka-VisualReacher.

  • GenRL

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a combination of reinforcement learning and generative models to solve...

  • Meta-World and Robomimic

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

  • DeepMind Control Suite

    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...

  • BBRL Activations Dataset

    The dataset used in the paper is a collection of activations from a feature extraction network and a reactive network, used to train a Variational Autoencoder (VAE) to learn...

  • D4RL Benchmark

    D4RL benchmark dataset, which consists of four offline logging datasets, collected by different one or mixed behavior policies.

  • Roboschool

    The dataset used in the ACE algorithm for continuous control problems.

  • D4RL

    D4RL datasets for maze2d-umaze, maze2d-medium, maze2d-large, antmaze-umaze, antmaze-medium, antmaze-large, parking, soccer-sim, and soccer-physical tasks

  • Gymnasium MuJoCo Benchmark

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

  • MuJoCo Benchmark

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

  • MuJoCo

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

  • OpenAI Gym

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used several continuous control environments from the OpenAI Gym.

  • CartPole

    The CartPole problem is a classic control problem in robotics and control theory. It is a simple, continuous control problem where a pole is attached to a mass on a cart, and...