# Recent Improvements in the Development of Soft Grippers
## 2 Soft Grippers
### Design, Fabrication, and Modeling  
Soft grippers are a subgroup of soft robots. As a result, they are designed and fabricated through soft robotics techniques. The manufacturing methods generally rely on additive manufacturing and 3D printing [6; 27; 35]. The soft actuators can either be casted using 3D-printed molds or directly fabricated using additive manufacturing techniques such as material extrusion, material jetting, VAT polymerization, as explained in [36]. The prototyping of soft robots is generally a faster process than for classical rigid robots, since the main methods used are said to be rapid and adaptable [27]. The simulation of soft robots is a growing field and its development could ease the design of prototypes for testing. The primary materials used in soft robotics have a Young's modulus ranging approximately between 10 kPa (e.g., gels and foams) and 1 GPa as noted in [37], and can be shaped with different topologies. Among them are found rubber, silicone, other elastomers, fabrics, foam, etc.  
A model of the system is often needed to study the behavior. Generally, the techniques of physical models for soft robots are constant curve approximation (CCA) [38] and exact geometric models [39]. When it comes to soft grippers, in order to characterize some parameters like the bending angle, the grasping performance, the actuation time, or the deformation with respect to the geometry and material properties, various modeling techniques have been used in the literature. For example, in [40], an analytical model of the gripper is constructed using a chain composite model of each pneumatic finger, the computation of strain energy and work performed by pressure, the gripper geometry, and coordinate transformation to analyze the grasping performance. In [41], they use the forward kinematics of the pneumatic actuator and homogeneous transformations to compute its displacement. The Neo-Hookean hyperelastic model is used to calculate material stretch moments. An approximative static mathematical model of the actuator can be derived based on the geometry and material properties, as performed in [42]. The Jacobian and neural network approaches are two methods of modeling tendon-driven actuators [6].  
Once the models have been created, simulations can be performed using the finite element method (FEM) with frameworks like SOFA, for example, ref. [43], or soft-volumetric pixel (called voxels) models with VoxCAD [6]. Simulations can allow the control of the grippers. For soft pneumatic fingers, the low-level approach control, i.e., the control of the internal pressure or volume of the actuators, is commonly used in soft grippers. For motor-driven actuation, the direct control of the motors is often applied to control the grippers.  
According to [5], soft grippers can be classified at the level of the grasping principle. This reference gives an idea of the principles with the different technologies applied: by actuation, by stiffness variation, and by adhesion. The reference also gives a general view of the performance of soft grippers by comparing the grasping principles in terms of the gripper/object weight relationship, the size of the gripper and the objects, the response time and the energy consumed, and the surface conditions required for the object.