OmniHand 3 Ultra-M
16 000 USD
AGILINK (Shanghai AGILINK Innovation Intelligent Technology Co., Ltd.)
OmniHand 3 Ultra-M is AGILINK’s flagship direct-driven dexterous hand — a 630g, 20-DoF, human-scale hand built for embodied AI training and research. With encoder-level ground-truth data, vision-based fingertip tactile sensing, and 300-point palm sensing, it’s engineered for continuous-duty, contact-rich manipulation work.
Hand Score
5
Specifications and details:
| Weight | 0.9 kg |
|---|---|
| Dimensions | 50 × 50 × 50 cm |
| Availability | In production |
| Degrees of freedom, hands | 20 |
| Strength [kg] | 8 |
| Weight [kg] | 0.63 |
| Size | 189.5 × 88.5 × 40 mm |
| Number of fingers | 5 |
| Tactile/Force Sensors | Fingertips use vision-based tactile sensors (3D distributed force + 6D resultant, texture recognition, 0–30N range, 0.005N resolution, 0.04mm spatial resolution), Palm uses a 3D tactile sensor with 300 tactile pixels at 0.1N resolution |
| Motor tech | Direct-drive at every joint (no tendons), with joint states read straight from each actuator's encoder for ground-truth positioning |
| Main structural material | Lghtweight alloy frame with engineering-polymer covers |
| Manufacturer | AGILINK (Shanghai AGILINK Innovation Intelligent Technology Co., Ltd.) |
| Nationality | China |
| Website | https://www.agilink-ai.com |
Description
OmniHand 3 Ultra-M is Agilink AI’s research-focused flagship, built where raw force density and data accuracy matter most. It packs 20 active joints into a 630-gram, human-scale hand, so it moves with real anatomical proportions. Because every joint uses direct-drive actuation, motion data comes straight from each encoder. As a result, the hand gives researchers and control systems trustworthy, ground-truth data instead of estimated positions. It also holds up under continuous use: the surface stays around 40–45°C under sustained load, and AGILINK has validated it through 500,000 cycles. Therefore, teams can run it hard during long training sessions without worrying about performance drift.
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Sensing is just as central to Ultra-M’s design. Vision-based tactile sensors sit in each fingertip, reading force, texture, and even subtle deformation across a wide force range. Consequently, the hand can tell the difference between a light touch and true contact, or between an edge and a flat surface. Additionally, 300 tactile points across the palm add another full layer of feedback for whole-hand awareness. This makes Ultra-M well suited for embodied AI training, teleoperation, and bimanual manipulation research. Overall, it pairs flagship-level dexterity with the precise, reliable data that advanced robotics research demands.
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Website: www.agilink-ai.com
