# Simulation Model for Robotic Pick-Point Evaluation for 2-F Robotic Gripper
## 3 Simulation Model for Object Pick-Point Evaluation
### Modeling Gripped Object  
Similarly, to modelling of the robotic gripper, the 3D model of the object to be gripped was also imported into ADAMS. The object was 3D scanned and postprocessed in a way that can be imported into the ADAMS/View software. Contact forces between the object and the surface and the static and dynamic friction were defined. We also defined the contacts between the robotic gripper's left finger and the object gripped along with the right finger. The contact theory used in the simulations in ADAMS is based on Hertzian Contact theory. Figure 4 shows a friction grip model, where each robotic gripper's fingers supply half of the required contact force. The minimal required grasping force, \(F_{G_{min}}\), applied by the gripper to the load can be calculated via the following equation:  
\[F_{G_{min}}=\frac{m\cdot g\cdot S_{f}}{2\cdot\mu_{s}} \tag{1}\]  
where \(m=\) mass of the object, \(g=\) gravitational acceleration (9.81 m/s\({}^{2}\)), \(S_{f}=\) safety factor, and \(\mu_{s}=\) static friction coefficient. Figure 3: Model of robotic gripper and the object to be gripped in ADAMS/View with different rotation settings. Source: Own. Figure 2: Model of robotic gripper and the object to be gripped in ADAMS/View. Green arrows (J1–J10) indicate revolute joints, yellow arrows (M1–M4) show rotational motions, cyan arrow (M5) indicates general motion (translation and orientation of the gripper), and red arrows indicate three different contacts used (C1–C3). Source: own. Of course, the minimal required grasping force increases as soon as the robotic gripper starts moving. The most significant factor in calculating the required grasping force is correctly determining the friction coefficient. Tables of friction coefficients between the individual elements were found in ADAMS Help section of the program, and the other parameters were set according to the real-time response of the simulations. Once the initial model and contact forces were established, measures were added to the model to check the influencing parameters (e.g., friction, contact forces, etc.). In addition, a marker was attached to the fingertip of the two-finger gripper to observe the object's distance from the surface. Furthermore, the object's rotation around the \(Y\)-axis was measured. Angular velocity and contact force measures were attached to the left and right robotic gripper fingers. Those variables served as the input of the force controller of the gripper closing. In our model, we defined the following input variables, which are managed via MATLAB/Simulink: (a) the closing speed of the left and right robotic gripper, (b) the final height of the robot gripper, (c) the start and end time of the robotic gripper, (d) initial speed of the robotic gripper, and (e) the initial translation and the rotation of the robotic gripper. The special feature of these variables is that they can be modified at run-time in MATLAB/Simulink. The initial location and orientation of the object and the robotic gripper can be set before the simulation starts by using the \"General Point Motion\" on the specific part(s) (Figure 5). However, we found that the model works best if the gripper's location and orientation are set using the MATLAB/Simulink variables, while the object's location and orientation are set manually by modifying the batch script (.adm file) prior to the simulation. Therefore, ADAMS models are changed using the MATLAB script by modifying ADAMS model files before running each simulation. While it is possible to obtain the coefficients of friction between the materials from the existing coefficient of friction tables, it is difficult to determine them accurately in a physical system. In addition, ADAMS models the transition from static to dynamic friction modes continuously rather than as it happens in reality (by jumping from one friction mode to another).