Optimal motion planning is very important to the operation of robot manipulators. Its main target is the generation of a trajectory from start to goal that satisfies objectives, such as minimizing path traveling distance or time interval, lowest energy consumption or obstacle avoidance and satisfying the robot’s kinematics and dynamics. Review, discussion and analysis of optimization techniques to find the optimal trajectory either in Cartesian space or joint space are presented and investigated. Optimal trajectory selection approaches such as kinematics and dynamics techniques with various constraints are presented and explained. Although the kinematics approach is simple and straight forward, it will experience some problems in implementation because of lack of Inertia and torque constraints. The application of Genetic Algorithms to find the optimal trajectory of manipulators especially in the obstacle avoidance is also highlighted. Combining the Genetic Algorithms with other classical optimization methods proves to have better performance as a hybrid optimization technique