Publication detail

Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

KREJSA, J. VĚCHET, S. RIPEL, T.

English title

Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

Type

Peer-reviewed article not indexed in WoS or Scopus

Language

en

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 in English

mobile robot, reactive navigation, artificial neural networks

Released

2013-01-01

ISSN

1012-0394

Journal

Solid State Phenomena

Volume

2013

Number

198

Pages from–to

108–113

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"
}