Publication detail

Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

KREJSA, J. VĚCHET, S. RIPEL, T.

Original Title

Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

Type

journal article - other

Language

English

Original Abstract

When mobile robots are used among people, the best accepted motion related behavior is a human-like motion of the robot. Such behavior is difficult to obtain with commonly used finite state machine based planners, but can easily be evoked when human controls the robot. The paper presents the way of transforming such knowledge from human controller to reactive planner in the robot navigation module. Reactive planner is based on machine learning, neural networks in particular. The planner consists of two separate neural networks, one serving as predictor of dynamic obstacles behavior, second one serving as the reactive planner itself, producing desirable actions of the robot both in terms of velocity and direction. Planner was verified on real robot producing human-like behavior when used in real environment.

Keywords

mobile robot, reactive navigation, artificial neural networks

Authors

KREJSA, J.; VĚCHET, S.; RIPEL, T.

RIV year

2013

Released

1. 1. 2013

ISBN

1012-0394

Periodical

Solid State Phenomena

Year of study

2013

Number

198

State

Swiss Confederation

Pages from

108

Pages to

113

Pages count

6

BibTex

@article{BUT103888,
  author="Jiří {Krejsa} and Stanislav {Věchet} and Tomáš {Ripel}",
  title="Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment",
  journal="Solid State Phenomena",
  year="2013",
  volume="2013",
  number="198",
  pages="108--113",
  issn="1012-0394"
}