This paper develops a variation of potential field algorithm for obstacle avoidance trajectory planning applied to an anthropomorphic manipulator of 6 degrees of freedom. In the first instance, the inverse kinematics model was generated based on a multivariate iterative control process, then the model was modified by adding a rotation vector obtained by the repulsive forces between the obstacle and the six joints of the robot so that the manipulator can find a route that avoids the obstacle and reaches a goal position. This final model of inverse kinematics with potential fields generates trajectories that depend on the optimization step size parameter and the vector fields coefficients. In order to optimize the trajectories, a database was generated with the initial, final and obstacle points of different trajectories with their respective parameters optimized to train a supervised neur...