Laith Erman
Soft robotic grippers have gained significant attention due to their ability to handle delicate and irregularly shaped objects, making them ideal for applications in industries such as food processing, medical assistance, and automated manufacturing. Unlike traditional rigid robotic grippers, soft robotic grippers leverage flexible and deformable materials to conform to the shape of the object being grasped. However, their compliance also introduces challenges in force control, as maintaining an optimal grip without damaging the object or losing hold requires precise and adaptive control strategies. To address this issue, the development of an adaptive force control strategy is essential for enhancing the performance and reliability of soft robotic grippers in dynamic environments. Adaptive force control enables soft robotic grippers to respond in real time to variations in object properties, external disturbances, and gripping conditions. This is achieved by integrating sensor feedback, control algorithms, and actuation mechanisms that dynamically adjust the gripping force based on real-time data
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