Autonomous vehicle navigation utilizing electrostatic potential fields and fuzzy logic

Author

Tsourveloudis, Nikos C. ; Valavanis, Kimon P. ; Hebert, Timothy

Author_Institution

Dept. of Production Eng., Tech. Univ. of Crete, Chania, Greece

Volume

17

Issue

4

fYear

2001

fDate

8/1/2001 12:00:00 AM

Firstpage

490

Lastpage

497

Abstract

An electrostatic potential field (EPF) path planner is combined with a two-layered fuzzy logic inference engine and implemented for real-time mobile robot navigation in a 2-D dynamic environment. The environment is first mapped into a resistor network; an electrostatic potential field is then created through current injection into the network. The path of maximum current through the network corresponds to the approximately optimum path in the environment. The first layer of the fuzzy logic inference engine performs sensor fusion from sensor readings into a fuzzy variable, collision, providing information about possible collisions in four directions, front, back, left and right. The second layer guarantees collision avoidance with dynamic obstacles while following the trajectory generated by the electrostatic potential field. The proposed approach is experimentally tested using the Nomad 200 mobile robot

Keywords

collision avoidance; fuzzy logic; inference mechanisms; mobile robots; motion control; sensor fusion; 2D dynamic environment; Nomad 200 mobile robot; approximately optimum path; autonomous vehicle navigation; collision avoidance; current injection; dynamic obstacles; electrostatic potential fields; path planner; real-time mobile robot navigation; resistor network; sensor fusion; two-layered fuzzy logic inference engine; Collision avoidance; Electrostatics; Engines; Fuzzy logic; Mobile robots; Navigation; Remotely operated vehicles; Resistors; Sensor fusion; Vehicle dynamics;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/70.954761

Filename

954761