● Introduction
Features
21 DoFs (16 active + 5 passive) mimic human hand movements and
grasping to meet complex, fine operation requirements.
●Multi-Modal Perception & Intelligent Interaction
Configurable with force and electronic skin sensors to accurately detect
contact force, object shape, and close-range images—boosting
environmental adaptability and interaction intelligence.
●Edge-Cloud Integration & No-Code Deployment
One-click skill deployment from cloud libraries via edge-cloud
architecture, lowering thresholds and improving efficiency.
●High Reliability & Data Support
Robust structure resists impact, adapting to high-intensity training and
industrial scenarios. It supports self-developed data collection for data
farm construction and algorithm optimization.
Robot Hand Interfaces
●Supported Robotic Arms: UR, Franka, XArm, RealMan, Songling
●Supported Data Acquisition Methods: teleoperation gloves, exoskeleton gloves, liquid metal gloves, vision, VR (Meta Quest 3)
●Supported Simulators: PyBullet, Isaac, MuJoCo
●Supported Interfaces: CAN, 485
●Example Applications: ROS1, ROS2, Python, C++
Specification
Sheet 1
Communication Methods
●CAN Interface
Utilizes a proprietary protocol; baud rate is 1Mbps; default device IDs: left hand 0x28, right hand 0x27; supports broadcast ID 0x7FF (for addressing, identification, and debugging).
●RS485 Interface
Adopts the Modbus protocol; baud rate is 256000bps; default device IDs: left hand 0x28, right hand 0x27; supports function codes: 03/04/06/16; UART settings are fixed: 8 data bits, 1 stop bit, no parity