# Design and Calibration of a Sensory System of an Adaptive Gripper
## 3 Results
### Testing the Grip for Implementation in Real Operations  
For real testing and simulation of grip quality, two types of solid objects were used--pieces with irregular shapes, for testing the effectiveness of the gripper and the performances of the sensors used. Figure 39a shows object number 1 used for the actual testing of the self-adaptive grip, and Figure 39b shows its grip position. Figure 40a shows object number 2, and Figure 40b shows its grasping with the self-adaptive gripper (b). The grasping was successfully performed, with each module of the grasper operating independently and correctly. In the following stages, it is necessary to optimize each module, a process that involves adjustments to the software specific to each module, depending on the data coming from its sensors. This optimization will contribute to improving the grasping process. All tests were performed without the grasper executing additional movements that would introduce inertial forces on the object or modules. Creating a well-defined logical architecture, with independent controllers for each grasper module, facilitated the implementation of self-adaptability. Individual control of the modules and quick decisions made by the Master controller contributed to the adaptability and reliability of the grasper under different grasping conditions. Implementing an efficient communication structure between the Master controller and the Slave modules allowed for precise and synchronized coordination of the grasping process. The ability to transmit simultaneous commands and collect essential data about the status of each module contributed significantly to the overall performance of the grasper. The implementation of a Master-Slave scheme in the gripper communication allows for centralized gripper control, ensuring efficient management of each module according to its specific status and requirements. This logical structure facilitates fast and accurate decisions-making during the gripper processes, contributing to the adaptability and efficiency of the system. The design and implementation of the control panel scheme facilitated precise control of the gripper, including the initiation, monitoring, and adjustment of the gripper according to the requirements of each object. In summary, the adaptive gripper, equipped with a PID algorithm system for each module, handles objects with irregular and unpredictable shapes through a combination of the following:  
Figure 40: Object number 2 (**a**) and bottom view of the grasp of object number 2 (**b**). Figure 39: Object number 1 used in testing (**a**) and its gripping position (**b**). Individual module control (each module has its own force sensor and its own PID controller). This allows for independent adaptation to the shape of the object. The modules adjust individually to conform to the contour of the object, ensuring multiple contact and uniform distribution of gripping force;
* Slip detection and compensation: Slip sensors instantly detect any unexpected movement of the object. The PID controller reacts immediately by adjusting the gripping force to prevent slipping. The rate of force change is controlled by the derivative component of the PID controller, ensuring a fast and precise response. Gripping force adaptation: Force sensors measure the gripping force applied to the object. The PID controller continuously adjusts the clamping force to maintain it at the desired value, compensating for variations in the shape and weight of the object. The integral PID controller component ensures precise compensation of persistent errors. Advanced control algorithms (potentially): Depending on the complexity of the implementation, more advanced control algorithms such as model-based control or machine learning algorithms could be used to improve the ability to adapt to complex and unpredictable shapes.