Techniahqrobot | humanoid robots(@techniahqrobot):LinkerBot is building robot hands that can move much closer to a human hand than a standard gripper. These clips show its dexterous-hand work across small-part handling, food manipulation finger coordination and grasping objects with very different shapes. One of LinkerBot’s current research hands the Linker Hand O30, has 20 fully active degrees of freedom, with all 20 joints controlled independently. It weighs 730 g, supports a rated payload of 30 kg, and produces up to 70 N of five-finger grip force. The O30 uses direct drive, communicates at 500 Hz through CAN or CAN FD, has ±0.20 mm repeat positioning accuracy, and opens or closes in 0.8 seconds. LinkerBot also specifies 24 N at the thumb tip and up to 30 N at each of the other fingertips. The food handling caught my attention most. An avocado, dough or other irregular object forces the hand to coordinate several contact points without crushing or dropping it. LinkerBot is also developing linkage driven and tendon-driven hands alongside the direct-drive O30, giving researchers several mechanical approaches for dexterous manipulation.

Techniahqrobot | humanoid robots@techniahqrobot

2026.09.21 10:40

LinkerBot is building robot hands that can move much closer to a human hand than a standard gripper. These clips show its dexterous-hand work across small-part handling, food manipulation finger coordination and grasping objects with very different shapes. One of LinkerBot’s current research hands the Linker Hand O30, has 20 fully active degrees of freedom, with all 20 joints controlled independently. It weighs 730 g, supports a rated payload of 30 kg, and produces up to 70 N of five-finger grip force. The O30 uses direct drive, communicates at 500 Hz through CAN or CAN FD, has ±0.20 mm repeat positioning accuracy, and opens or closes in 0.8 seconds. LinkerBot also specifies 24 N at the thumb tip and up to 30 N at each of the other fingertips. The food handling caught my attention most. An avocado, dough or other irregular object forces the hand to coordinate several contact points without crushing or dropping it. LinkerBot is also developing linkage driven and tendon-driven hands alongside the direct-drive O30, giving researchers several mechanical approaches for dexterous manipulation.

Techniahqrobot | humanoid robots@techniahqrobot

2026.09.19 12:08

Sharpa Robotics just dropped a new hand video and the level keeps going up. This is the Sharpa Wave running WM Craftnet on a human scale fivefinger hand with 22 active DoF. The policy combines wrist depth, tactile sensing, proprioception and previous actions. The hand can rotate different objects in-hand, recover after external pushes and continue manipulating objects it was never trained on. The numbers are strong. 175/200 successful real-world rotation trials across 20 objects. A world-model prior trained on 9 objects was transferred to 49 new objects. Fall rate went from 6% to 0.3%. The Wave hardware itself has 22 actuators, up to 20 N fingertip force, 240×240 tactile sensing at up to 180 fps and 0.02 N pressure sensitivity. What caught my attention is the recovery behavior. The fingers keep changing contact points after the object slips or gets pushed instead of replaying the same finger motion. That is the kind of dexterity I want to see more of in robotic hands. According to Sharpa’s current specifications: • DTA tactile sensors on the fingers with a resolution of up to 240 × 240 • Pressure detection • Slip detection • Force change detection • Contact point localization • 6-axis force and torque measurement: Fx, Fy, Fz, Mx, My, Mz • Tactile sensing at up to 180 fps • 20 ms reported latency • Force detection range from 0 to 30 N • Maximum sensor load of 50 N • Sharpa also describes a miniature camera integrated into each fingertip for visuo-tactile sensing.