The AgiBot OmniHand Pro 2025 is an anthropomorphic five-finger dexterous robotic hand by AGIBOT (AgiBot Innovation Shanghai Technology Co., Ltd.). It features 19 degrees of freedom (12 active, 7 passive), weighs approximately 820 g, and achieves 0.4 mm positioning repeatability. Designed for contact-rich manipulation, it is compatible with major collaborative and humanoid robot platforms via CAN FD interface.
Primary use case: Dexterous manipulation for humanoid and collaborative robot research, including grasping, sorting, and contact-rich assembly tasks.
Price
$15K
Locomotion
stationary
Max Speed
4.32 km/h
Max Lift/Arm
35 kg
AI Capabilities
intelligent interaction, autonomous operation, facial recognition, autonomous navigation, intelligent obstacle avoidance, swarm control planning
Price
$15K
Availability
available
Primary Use Case
Dexterous manipulation for humanoid and collaborative robot research, including grasping, sorting, and contact-rich assembly tasks.
AGILINK's OmniHand 3 Ultra robot hand is learning to perform Suzhou embroidery, a 2,500-year-old craft, by splitting silk threads into 16 finer strands, threading needles, and stitching fabric. The dexterous hand features 21 degrees of freedom, 630g weight, 8kg lifting capacity, and sub-millimeter sensing capabilities. The article also chronicles AGILINK's growth from an AGIBOT subsidiary in 2023 to an independent unicorn valued over $1 billion, having shipped more than 15,000 dexterous hand units.
IDC data shows AGIBOT led global humanoid robot shipments in H1 2026, shipping more than 8,600 units—approximately 35% of global shipments of nearly 25,000 units (up 432.1% YoY). The article highlights AGIBOT's milestone of 20,000 cumulative robots produced by September 2026, along with large-scale deployments at Chimelong Spaceship Park (300+ robots) and ASD retail stores (100 AGIBOT X2 units).
AGIBOT demonstrated its WITA-Omni embodied-native omni-modal model at the Greater Bay Area Film Concert, where robots interacted face-to-face with a celebrity in real-time by identifying speakers, coordinating speech, movement, and expressions dynamically rather than following scripted sequences. The model uses a Thinker-Talker-Actor architecture that aligns speech and physical behavior along the same timeline, achieving top benchmark performance on the DailyOmni evaluation.