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Techniahqrobot | humanoid robots
@techniahqrobot
humanoid robots | Automation | AGI | ASI | Tracking the rise of autonomous systems and the future of intelligence Physical AI embodied
Joined October 2021
946 Following    18.1K Followers
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.
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Two very different projects. Same kind of engineering instinct. The upper clip uses a cockroach with a very minimal mechanical setup. The lower one takes a quadcopter and surrounds it with tracked frames so the same machine can move on land, travel through water and take off into the air. What caught my eye is how both designs start from a physical behavior instead of adding layers of software. For the air land water drone the engineering tradeoff is especially interesting. Flying helps with obstacles and speed. Driving can save battery when the terrain allows it. Water mobility gives the same platform another route when roads disappear. Of course, every extra mobility mode adds weight, moving parts and harder control transitions. Still I like this direction. Build the machine around the environment it has to cross. I’m still wondering what the cockroach project in the top clip is actually meant to do though. Does anyone know the intended use case?
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