Open AccessPath Planning Based on Fuzzy Decision Trees and Potential Field
Author(s) -
Iswanto Iswanto,
Oyas Wahyunggoro,
Adha Imam Cahyadi
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i1.pp212-222
Subject(s) - maxima and minima , motion planning , computer science , shortest path problem , fuzzy logic , robot , path (computing) , artificial intelligence , decision tree , field (mathematics) , robotics , graph , mathematical optimization , algorithm , mathematics , theoretical computer science , mathematical analysis , pure mathematics , programming language
The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.