Implementation of Improved Artificial Potential Field Path Planning Algorithm in Differential Drive Mobile Robot

Abstract

An autonomous mobile robot (AMR) with wheel drive is one of the most widely developed applications today. Navigation ability, especially path planning, is one of the problems faced in AMR development. One of the path planning algorithms that is considered reliable and can be implemented in real-time is the artificial potential field (APF). However, the weakness of APF is that the robot can be trapped in the minimum locale. The local minimums commonly encountered are goal non-reachable due to nearby obstacles (GNRON) and symmetrically aligned robot obstacle goals (SAROG). This study aims to develop an APF-based path planning algorithm to solve the local minimum problem. The Gompertz function and the cone-shaped potential field are used in the Improved APF (IAPF) algorithm. The IAPF algorithm is also implemented in the kinematic equation of a wheeled mobile robot with a differential drive type. The results show that the IAPF algorithm can be implemented in a differential drive type robot. The robot can avoid obstacles in the form of SAROG and GNRON and go to the goal with an error to the goal $(d_{rg})$ less than the tolerance value of 5%.