In this paper, the solution of inverse kinematics problem of robot manipulators using genetic algorithms (GA) is presented. Two versions of genetic algorithms are used which include the conventional GA and the continuous GA. The inverse kinematics problem
is formulated as an optimization problem based on the concept of minimizing the accumulative path deviation in the absence of any obstacles in the workspace. Simulation results show that the continuous GA outperforms the conventional GA from all aspects. The superiority of the continuous GA is seen in that it will always provide smooth and faster solutions as compared with the conventional GA.