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因子图
一种概率图模型，其中变量节点（要估计的状态）和因子节点（来自测量的约束）通过边连接。因子图上的推理（寻找最大后验估计）解决SLAM和传感器融合问题。GTSAM和g2o为实时SLAM实现了高效的稀疏因子图优化。
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.
一种概率图模型，其中变量节点（要估计的状态）和因子节点（来自测量的约束）通过边连接。因子图上的推理（寻找最大后验估计）解决SLAM和传感器融合问题。GTSAM和g2o为实时SLAM实现了高效的稀疏因子图优化。