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.
不仅考虑期望回报，还考虑结果方差或尾部风险的强化学习。CVaR（条件风险价值）优化最小化最坏情况性能而非平均性能。风险感知强化学习对物理机器人很重要，因为即使以平均性能为代价，也必须避免罕见的灾难性结果（硬件损坏、人员伤害）。
