A univariate marginal distribution algorithm based on extreme elitism and its application to the robotic inverse displacement problem

作者：Gao Shujun^*; de Silva Clarence W

来源：Genetic Programming and Evolvable Machines, 2017, 18(3): 283-312.

DOI：10.1007/s10710-017-9298-8

• Univariate marginal distribution algorithm
• Inverse displacement problem
• Top best solutions
• Gaussian model
• Differential evolution algorithm

In this paper, a univariate marginal distribution algorithm in continuous domain (UMDA (C) ) based on extreme elitism (EEUMDA (C) ) is proposed for solving the inverse displacement problem (IDP) of robotic manipulators. This algorithm highlights the effect of a few top best solutions to form a primary evolution direction and obtains a fast convergence rate. Then it is implemented to determine the IDP of a 4-degree-of-freedom (DOF) Barrett WAM robotic arm. After that, the algorithm

• 出版日期2017-9