Path Planning is one of the vital aspects in autonomous system. In path planning, safety is important issue that
should be taken into account in order to ensure a robot reaches at the target location without collision with surrounding
obstacles. Moreover, there are important aspects that need to be addressed in path planning; computational time, optimal
path and completeness. One of the popular methods for path planning is Potential field. Potential filed method is capable to
overcome unknown scenario, taking into account the realities of the current environment of the robot motion. Two type of
forces involved in potential field method; attractive force generated by goals and repulsive force generated by obstacles.
However, this method has a major drawback due to local minima problem. This paper reviews the traditional artificial
potential field theory that has been modified with variety of algorithms based on potential field method that have been
implemented to upgrade the potential function performance in obstacle avoidance and local minima problem
