Abstract
Grasping various shaped objects poses a few challenges such as irregular shapes, soft surfaces, and varying sizes of the object. To enable the gripper to overcome these challenges, this paper proposes the use of multi-fingered soft grippers. The main objective of this research work is to optimize the gripping force and surface area of contact through an experimental and computational study of an automated multi-fingered adaptive soft gripper. Deflection, stress distribution, and pressure distribution for three and four-fingered grippers are compared computationally. The experimental investigation is performed to optimize inlet pneumatic pressure, and the contact force applied on the object by the gripper. A gripper failure protection mechanism is also devised and employed which regulates the over-expansion of the gripper by incorporating a closed-loop feedback mechanism with the help of an FSR sensor which not only regulates the input pressure while gripping but also prevents the gripper from exerting excess pressure on the object being gripped. Optimization reliability tests were validated and revealed that the test results were within the estimated level of confidence. A Fuzzy logic model was created based on Experimental results on three-finger flexible gripper actuation on a Robot and predicted the optimum results accurately with the high confidence level.
Get full access to this article
View all access options for this article.