Design Optimization of Pneumatically Actuated Three Jaw Gripper Using Genetic Algorithm

Abstract

Design optimization of grippers should be decisive for felicitous applications, definitive results, and for the implementation to be efficacious. This paper concentrates on mathematical modelling of a three-jaw gripper, to procure the fundamental design parameters that are crucial for design constraints. Multi-objective design optimization formulation is adapted to calibrate multi-constraint design variables, to optimally obtain the dimensions of the links and dimensions of the actuating cylinder. The Gripper is analyzed for dynamic modelling, to compute gripping-force and gripping-width with precision. Compromised solution based on objective function formulation is applied, where the population is generated with genetic algorithm. This would deduce the optimal solution set among the generated population and the control variables are regulated by establishing a relation between decision variables and objective functions, such that we acquire better gripper ratio, gripper force analysis as wells design sensitivity analysis.