Open 7-DoF arm, bimanual-ready. Ships from San Francisco with pilot data-collection packages from $2,500.
90+ platforms — humanoids, arms, quadrupeds, dexterous hands, and teleoperation kits. In-stock hardware ships in 48 hours.
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.
Low-latency data-collection glove for dexterous manipulation. From $5,500, ships from San Francisco.
Unbox, calibrate, and run your first autonomous walk. Includes ROS 2 bringup and teleop quickstart.
将完全在仿真中训练的控制策略部署到物理机器人上。仿真-现实差距(物理、渲染和传感器模型的差异)通过域随机化、系统辨识和域适应来弥合。仿真到现实是基于强化学习的运动控制的主流范式,在操作任务中也越来越常见。成功取决于仿真保真度和随机化策略。