Tag: Dexterous Manipulation

Sep 14
Teleoperation Workstations: Inside the VR and Exoskeleton Rigs Used to Collect Training Data

Before a Vision-Language-Action (VLA) foundation model or Diffusion Policy can autonomously seat an electrical connector or manipulate heavy dunnage, it must observe hundreds of high-fidelity physical demonstrations. Because simulation still struggles with micro-scale contact dynamics, soft-tissue deformations, and oily surface friction, high-precision human teleoperation remains the gold standard for collecting real-world robotic demonstration datasets. Yet, […]

Sep 14
Imitation Learning vs. Reinforcement Learning: Which Yields Better Dexterous Manipulation?

Building an anthropomorphic humanoid hand with 16 to 24 degrees of freedom is an extraordinary mechatronic achievement. Controlling it to perform high-dexterity industrial tasks—such as seating a rubber O-ring into a groove, threading an M6 bolt into a blind hole, or manipulating a flexible wiring harness—remains the hardest software challenge in robotics. Unlike bipedal locomotion, […]

Sep 11
Sanctuary AI Phoenix: Inside the Hydraulic Micro-Actuator Approach to Hand Dexterity

In the contemporary humanoid landscape, an engineering consensus appears to have solidified around electromechanical actuation. Almost every high-profile developer—from Tesla and Figure to Unitree and 1X—has standardized on brushless DC motors mated to planetary, cycloidal, or tendon-driven transmissions. The industry-wide thesis is straightforward: electric systems are clean, quiet, highly efficient, and easily integrated into solid-state […]