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    Home»Robotics»AI Robotics Unicorn Sharpa and NVIDIA Bridge the Simulation Hole for Dexterous Robotic Coaching
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    AI Robotics Unicorn Sharpa and NVIDIA Bridge the Simulation Hole for Dexterous Robotic Coaching

    Arjun PatelBy Arjun PatelMarch 15, 2026No Comments3 Mins Read
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    AI Robotics Unicorn Sharpa and NVIDIA Bridge the Simulation Hole for Dexterous Robotic Coaching
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    Sharpa goals to speed up the deployment of robots able to advanced manipulation duties throughout shopper and enterprise markets.

    Sharpa presents new analysis demonstrating important enhancements in simulation strategies for robotic coaching, in collaboration with NVIDIA.

    Sharpa goals to speed up the deployment of robots able to advanced manipulation duties throughout shopper and enterprise markets. To realize human-like dexterity, Sharpa leverages simulation both by coaching the robotic on single duties utilizing Reinforcement Studying (RL) in digital environments; or by producing artificial information used to pre-train its Imaginative and prescient Tactile Language Mannequin (VTLA). Commonplace tactile simulations usually pressure a alternative between bodily authenticity and computation velocity. Tacmap, a simulation framework developed in cooperation with NVIDIA, solves this situation by means of a shared, high-fidelity geometric illustration. The simulation and code belongings can be open sourced to unfold the learnings with the broader robotics neighborhood.

    “This collaboration strengthens the inspiration for coaching in simulation, advancing the robotics subject in direction of extra dexterity and autonomy and accelerating large-scale deployment,” stated Alicia Veneziani, International VP of Go-To-Market and President of Europe at Sharpa.

    As well as, Sharpa is proud that its dexterous hand Wave has been chosen by NVIDIA to advance analysis on information environment friendly studying. NVIDIA’s GEAR Lab researchers efficiently transferred insurance policies, obtained from pre-training GR00T mannequin on 20,000+ hours of human movies, to robots outfitted with Sharpa’s Wave palms. The robots have been capable of full duties like assembling mannequin vehicles, working syringes, and sorting playing cards with a 54% increased success price, proving that video data-based coaching could be successfully scaled on robots with extremely anthropomorphic palms.

    Sharpa, a recipient of the iF Product Design Award, and CES Innovation 2026 Award, will current its dexterity-first, full stack options at GTC 2026, demonstrating how human-like palms coupled with tactile VTLA can speed up the deployment of productive robots. Sharpa is happy to announce its membership within the NVIDIA Inception program.

    North, a general-purpose humanoid robotic integrating whole-body management and effective loco-manipulation
    Wave, a human-scale robotic hand engineered with 22 energetic levels of freedom and tactile sensors
    CraftNet, a VTLA mannequin together with a Movement Mind (System 1) that directs actions and an Interplay Mind (System 0) that governs the contact with objects, enabling millimeter-level precision interplay. Craftnet optimises coaching information by mapping tactile indicators onto human video and glove-acquired information.
    To know extra, discover Sharpa on the GTC 2026 Convention:

    Sales space #1838, Corridor 3, San Jose McEnery Conference Middle,
    150 W San Carlos St,
    San Jose, CA 95113, USA.

    Media interviews, product demonstrations, and workplace tour alternatives at Mountain View workplace can be found upon request.

    About Sharpa

    Based in 2024, Sharpa is a unicorn AI robotics firm devoted to creating high-performance dexterous robots, methods and parts for general-purpose purposes. Sharpa’s mission is to construct robots that free individuals from repetitive or strenuous work to give attention to extra significant pursuits. Sharpa’s international headquarters is in Singapore, with manufacturing R&D in Shanghai and enterprise operations in Mountain View, USA.

    www.sharpa.com

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    Arjun Patel
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