The Dexterity Gap in Robotics
The gap between what a robot can think and what it can physically do has long been a central limitation of practical robotics. AI systems have achieved remarkable capabilities in planning, reasoning, and responding to visual and tactile inputs, but translating that intelligence into fine motor control — the kind that allows a human to thread a needle, catch a falling glass, or sort mixed items by touch — has remained one of the hardest engineering problems in the field. The end effector, the hand at the end of a robot arm, is where intelligence meets the physical world, and most current designs fall far short of human capability.
Tesollo, a South Korean company specializing in dexterous robotic hands and grippers, has introduced a device designed to close that gap significantly. The DG-5F-S is a five-finger robotic hand with 20 degrees of freedom, engineered to replicate human-like articulation within the size and weight constraints required for integration into humanoid robot platforms. At under 900 grams (approximately 2 pounds), it is designed to sit at the end of a humanoid robot's arm without disrupting the system's balance and dynamics.
Technical Specifications
The 20 degrees of freedom in the DG-5F-S represent a substantial advance over most commercial robotic hands, which typically offer between 6 and 12 degrees of freedom. Each degree of freedom corresponds to an independent joint axis — a direction in which part of the hand can independently flex, extend, or rotate. With 20 DoF across five fingers, the DG-5F-S can produce a much wider range of grasp configurations and manipulation movements than simpler designs, including the pinch grasps, power grips, and dexterous in-hand manipulations that characterize human hand use.
The actuation system uses a combination of electric motors and tendon-driven mechanisms — a design approach that borrows from the anatomy of the human hand, where muscles in the forearm transmit force to finger joints through tendons. This distributed actuation strategy keeps weight out of the fingers themselves, improving the hand's dynamic performance and making it less vulnerable to damage from impacts.
