Exponential navigation functions with a learning algorithm

K. Bendjilali, F. Belkhouche, T. Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper suggests a method for autonomous wheeled mobile robots navigation under the nonholonomic constraint. The suggested method uses navigation functions that are based on the polar kinematics equations, where the steering angle and the orientation angle of the robot are included in an exponential function of the line of sight angle. Another control law is suggested for the robot's linear velocity to drive the robot to a desired position with a desired final orientation angle. The exponential navigation functions depend on various navigation parameters that allow to change the robot's path. This approach is combined with the collision cone technique to avoid collision. A Q-learning algorithm is suggested to select automatically the appropriate values of the navigation parameters. Simulation is used to illustrate the method.

Original languageEnglish (US)
Title of host publication2008 American Control Conference, ACC
Pages1232-1237
Number of pages6
DOIs
StatePublished - 2008
Event2008 American Control Conference, ACC - Seattle, WA, United States
Duration: Jun 11 2008Jun 13 2008

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2008 American Control Conference, ACC
CountryUnited States
CitySeattle, WA
Period6/11/086/13/08

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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