Whether gripping, holding or turning, touching, typing or pressing – we use our hands for a wide variety of tasks in our everyday lives without thinking twice about it. The human hand is a true miracle tool of nature. What could be more logical than equipping robots in collaborative workspaces with a gripper that is inspired by this natural model and can learn through artificial intelligence to solve a wide variety of gripping and turning tasks?
The BionicSoftHand uses methods of reinforcement learning. This means that instead of having to imitate a concrete action, the hand is merely given a goal. It tries to achieve this through trial and error. Based on the positive and negative feedback received, the hand gradually optimises its actions until it finally solves the task successfully.
The BionicSoftHand is tasked with rotating a dodecahedron so that a previously defined side faces upwards at the end. The necessary movement strategy is taught in a virtual environment with the aid of a digital twin, which is created using data from a depth-sensing camera and artificial intelligence algorithms.
Digital twin: the real robot hand and its virtual representation in the simulation model
The digital simulation model speeds up the training considerably, especially if you multiply it. In massively parallel learning, the acquired knowledge is shared with all of the virtual hands, which then continue to work with the new state of knowledge, meaning that each error is only made once. Successful actions are immediately available to all models.
Once the control system has been trained in the simulation, it is transferred to the real BionicSoftHand. This can then use the movement strategy learned in the virtual environment to turn the object the desired way around and orient other objects accordingly in the future. Knowledge building blocks and new skills, once learned, could then also be shared with other robot hands and made available globally.
Unlike the human hand, the BionicSoftHand does not have any bones. It controls its movements via the pneumatic bellows structures in its fingers. When the chambers are filled with air, the fingers bend. If the air chambers are empty, the fingers remain stretched. The thumb and index finger are additionally equipped with a swivel module, which allows these two fingers to also be moved laterally. This gives the bionic robot hand a total of twelve degrees of freedom.
The bellows in the fingers are enclosed in a special 3D textile cover knitted from both elastic and high-strength fibres. This means that the textile can be used to exactly determine at which points the structure expands, thereby generating force, and where it is prevented from expanding.
In order to keep the amount of tubing work required for the BionicSoftHand as low as possible, the developers have specially designed a small, digitally controlled valve terminal, which is mounted directly below the hand. This means that the tubes for controlling the fingers do not have to be pulled through the entire robot arm. As a result, the BionicSoftHand can be quickly and easily connected and operated with only one tube each for supply air and exhaust air. The proportional piezo valves used enable the movements of the fingers to be precisely controlled.
Its flexible, pneumatic kinematics and the use of elastic materials and lightweight components make the BionicSoftHand stand out from electric or cable-operated robot hands and enable inexpensive production. Their modular design means that gripper variants with three or four fingers are also possible.
Combined with pneumatic lightweight robots – such as the BionicCobot or the BionicSoftArm – the robot hand can be used for safe and direct human–robot collaboration. Both robots are designed with pliability throughout and do not need to be shielded from the worker like conventional factory robots.
This makes the BionicSoftHand ideal for applications in collaborative workspaces in the factory of the future. Since the flexible robot hand can grip with both strength and sensitivity, it could conceivably be used in assembly as a helping third hand and also in service robotics.