# 2.1.1. suitable forces are applied that will

2.1.1. Potential Field
Method

Potential field can be imagined as the
differential of attraction and repulsion factors 42. The
idea behind potential field is taken from nature. For instance a charged
particle navigating a magnetic field, or a small ball rolling in a hill,
depending upon idea is the strength of the field, or the slope of the hill, the
particle, or the ball can arrive to the source of the field, the valley or the
magnet in this example. In robotics, by creating an artificial potential field
that will attract the robot to the goal can be simulated with the same effect.
By designing adequate potential field, we can develop the robot exhibit simple
behaviors. For example, let’s assume that there is no obstacle in the
environment, and that the robot should search for this goal. If we work in
conventional planning then one should calculate the relative position of the
robot to the goal, and then suitable forces are applied that will drive the
robot to the goal.

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Fig.
1. Attraction and repulsion by target and obstacle

In potential field method, we simple generate an attractive filed going
inwards the goal. The potential field is distinct across the complete free
space, and in each time step, at the robot position we calculate the potential
filed, and then calculate the induced force by this field. Then according to
this force robot should move. We can also define
another behaviour that allows the robot to avoid obstacles. We merely build
each obstacle produce a repulsive field around it. If the robot approaches the
obstacle, a repulsive force will act on it, pushing it away from the obstacle.

Attractive / Repulsive Potential field is given as: U (q) =

Where,

is attractive potential which moves to goal,

is repulsive potential avoid obstacles. Potential Field method and its modified versions are commonly used
as motion controller of robots in obstacle avoidance scenarios 37, 38, 39, 40,
and 41. Cetin et al. 43 discussed the utilization of Artificial Potential
Field, Jaradat et al. 44 used a fuzzy-based Potential Field, Subramanian et
al. 45 employed multipoint potential field in an obstruction prevention
problem, Song 47 used decentralized Potential Field-based controllers, Valbuena
and Tanner 46 gives the application of the Potential Field for collision
avoidance and motion planning in non-holomonic mobile robots, Bence Kovacs et
al. 15 proposed method is that, by adapting natural motion attributes of
animals to robot motion, the human-robot interaction becomes much more natural
and intuitive. It also becomes easy to understand the robot’s current state and
future intentions.