Description: An improved genetic algorithm for solving the inverse problem of manipulator kinematics. The algorithm uses real number encoding, the crossover probability and mutation probability according to the fitness function value of solution adaptive. Computer simulation results show that the algorithm is relatively simple genetic algorithm for (SGA) for solving high precision, fast convergence and stable performance is good.
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