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Design Optimization of Robot Gripper Using Intelligent Techniques (GA & DE)
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This paper concerns with the use of intelligent techniques such as Genetic Algorithm (GA) and Differential Evolution (DE) to find optimum geometrical dimensions of a robot gripper. The problem is finding a combined objective function, which has five objectives, seven constraints and five variables. The objective functions are difference between maximum and minimum griping forces, force transmission ratio between gripper actuator and gripper ends, shift transmission ratio between gripper actuator and gripper ends, length of all elements of gripper and efficiency of gripper mechanism. The problem is dealt with three cases. A very original, new optimization model is derived and used. Also, a comprehensive user-friendly general-purpose software package has been developed to obtain the optimal parameters using the proposed DE algorithm.
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