97 datasets found

The Humanoid Walk dataset is a collection of images of a humanoid robot performing various tasks.

A dataset used for training a recurrent neural network (RNN) to infer positional uncertainties for a model predictive control (MPC) algorithm.

The Desk Cleanup environment, which consists of a robotic arm and several blocks on a desk.

The Fetch Manipulation environment with 3 blocks, which consists of a robotic arm with a gripper and three blocks.

The Fetch Manipulation environment with 2 blocks, which consists of a robotic arm with a gripper and two blocks.

The Fetch Manipulation environment built on top of Mujoco, which consists of a robotic arm with a gripper and square blocks.

The dataset used for training and testing the proposed localizability estimation approach.

The dataset used in the paper is a set of data collected from the Sawyer robot.

The dataset used in the paper is a set of data collected from the OpenAI Gym Reacher environment.

The Oxford Radar Robotcar Dataset is a radar extension to the Oxford Robotcar Dataset, containing data collected from a scanning Navtech radar in various weather conditions.

Shared autonomy is an operational concept in which a user and an autonomous agent collaboratively control a robotic system. It provides a number of advantages over the extremes...

Grasp-Anything++ is a large-scale language-driven grasp detection dataset featuring 1M samples, over 3M objects, and upwards of 10M grasp instructions.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

TUM-MLS-2016: An annotated mobile lidar dataset of the TUM City Campus for semantic point cloud interpretation in urban areas.

Developing and testing robust autonomy: The university of sydney campus data set.

The dataset used in this paper is the PyBullet Environments.

Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation

Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation