Artificial Potential Field Algorithm Implementation for Quadrotor Path Planning

Abstract

Potential field algorithm introduced by Khatib is well-known in path planning for robots. The algorithm is very simple yet provides real-time path planning and effective to avoid robot's collision with obstacles. The purpose of the paper is to implement and modify this algorithm for quadrotor path planning. The conventional potential method is firstly applied to introduce challenging problems, such as not reachable goals due to local minima solutions or nearby obstacles (GNRON). This will be solved later by proposed modified algorithms. The first proposed modification is by adding virtual force to the repulsive potential force to prevent local minima solutions. Meanwhile, the second one is to prevent GNRON issue by adding virtual force and considering quadrotor's distance to goal point on the repulsive potential force. The simulation result shows that the second modification is best applied to environment with GNRON issue whereas the first one is suitable only for environment with local minima traps. The first modification is able to reach goals in six random tests with local minima environment. Meanwhile, the second one is able to reach goals in six random tests with local minima environment, six random tests with GNRON environment, and six random tests with both local minima and GNRON environment.

Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment

“…In the UAV, there are controllers that help the robot to reach the set point from APF. It can be a PID control [50], state feedback [49], fuzzy logic [51] [52], or another controller [53][54] [55].…”

“…Therefore, this study aims to compare the performance of modified APF algorithms in challenging various obstacles with local minima. In the research, the conventional APF [26][27], modified APF [47], optimized APF [48], and APF with virtual force [49] will be compared to know its performances in navigating for a dynamic and unknown environment.…”

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“…One type of UAV (unnamed Aerial Vehicle) that is currently being studied is a quadcopter [3]. A helicopter type UAV that uses four motors to move the propeller.…”

Embedded Control System of DC Motor Using Microcontroller Arduino and PID Algorithm

“…DC motors have many applications in the field of robotics [1][2] [3] and industrial applications [4][5] [6]. Some examples of implementation are tracking systems for the direction of the sun [7], balance robot [8] [9], line follower robot [10] [11], line maze robot [12] [13], Quadrotor [14] [15], temperature control [16], Omni Robot [17] etc. DC motors are very popular because they are easy to learn, easy to control, and have good performance.…”