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.
在不进行完全重新训练的情况下，向现有机器人学习系统添加新知识（任务、物体、环境）。增量学习方法必须平衡可塑性（学习新事物的能力）和稳定性（保留旧知识）。实际上，机器人的增量学习涉及仔细的数据集管理、正则化和模块化架构设计。
