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.
一种损失函数，用于衡量预测概率分布与真实标签之间的差异。对于分类任务，它是正确类别的负对数似然。在机器人学习中，交叉熵用于离散动作预测、VLA模型中的令牌生成以及训练语言条件控制策略，其中动作空间被离散化。
