Open 7-DoF arm, bimanual-ready, with pilot data-collection packages.
90+ platforms — humanoids, arms, quadrupeds, dexterous hands, and teleoperation kits. Lead time shown on each product.
Hardware-synced demonstrations for VLA and imitation learning. Download in LeRobot, HDF5, or RLDS format.
From first arm on the bench to a policy that survives a real workcell — the Robotics Center pipeline in three steps.
Specifications and integration guide for the tactile and pose-tracking data glove.
Unbox, calibrate, and run your first autonomous walk. Includes ROS 2 bringup and teleop quickstart.
一个神经网络，用于从状态-动作对或轨迹段预测标量奖励值，通常基于人类偏好或专家演示进行训练。奖励模型用学习的奖励函数替代手工设计的奖励函数。它们是RLHF风格训练的核心，在机器人学中用于指定难以数学形式化的复杂任务目标。
