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Imitation learning of an intelligent navigation system for mobile robots using reservoir computing

Eric Antonelo UGent, Benjamin Schrauwen UGent and Dirk Stroobandt UGent (2008) 2008 10th Brazilian symposium on Neural Networks (SBRN 2008). p.93-98
abstract
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which must be overcome. Reservoir Computing (RC) uses a randomly created recurrent neural network (the reservoir) which functions as a temporal kernel of rich dynamics that projects the input to a high dimensional space. This projection is mapped into the desired output (only this mapping must be learned with standard linear regression methods). In this work, RC is used for imitation learning of navigation behaviors generated by an intelligent navigation system in the literature. Obstacle avoidance, exploration and target
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
neural networks, imitation learning, reservoir computing
in
2008 10th Brazilian symposium on Neural Networks (SBRN 2008)
pages
93 - 98
publisher
IEEE
place of publication
Piscataway, NJ, USA
conference name
10th Brazilian symposium on Neural Networks (SBRN 2008)
conference location
Salvador, Bahia, Brazil
conference start
2008-10-26
conference end
2008-10-30
Web of Science type
Conference Paper
Web of Science id
10384906
ISSN
1522-4899
ISBN
9781424432196
9780769533612
DOI
10.1109/SBRN.2008.32
language
English
UGent publication?
yes
classification
C1
id
678220
handle
http://hdl.handle.net/1854/LU-678220
date created
2009-06-04 15:01:51
date last changed
2011-07-28 14:24:03
@inproceedings{678220,
  abstract     = {The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which must be overcome. Reservoir Computing (RC) uses a randomly created recurrent neural network (the reservoir) which functions as a temporal kernel of rich dynamics that projects the input to a high dimensional space. This projection is mapped into the desired output (only this mapping must be learned with standard linear regression methods). In this work, RC is used for imitation learning of navigation behaviors generated by an intelligent navigation system in the literature. Obstacle avoidance, exploration and target},
  author       = {Antonelo, Eric and Schrauwen, Benjamin and Stroobandt, Dirk},
  booktitle    = {2008 10th Brazilian symposium on Neural Networks (SBRN 2008)},
  isbn         = {9781424432196},
  issn         = {1522-4899},
  keyword      = {neural networks,imitation learning,reservoir computing},
  language     = {eng},
  location     = {Salvador, Bahia, Brazil},
  pages        = {93--98},
  publisher    = {IEEE},
  title        = {Imitation learning of an intelligent navigation system for mobile robots using reservoir computing},
  url          = {http://dx.doi.org/10.1109/SBRN.2008.32},
  year         = {2008},
}

Chicago
Antonelo, Eric, Benjamin Schrauwen, and Dirk Stroobandt. 2008. “Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing.” In 2008 10th Brazilian Symposium on Neural Networks (SBRN 2008), 93–98. Piscataway, NJ, USA: IEEE.
APA
Antonelo, E., Schrauwen, B., & Stroobandt, D. (2008). Imitation learning of an intelligent navigation system for mobile robots using reservoir computing. 2008 10th Brazilian symposium on Neural Networks (SBRN 2008) (pp. 93–98). Presented at the 10th Brazilian symposium on Neural Networks (SBRN 2008), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Antonelo E, Schrauwen B, Stroobandt D. Imitation learning of an intelligent navigation system for mobile robots using reservoir computing. 2008 10th Brazilian symposium on Neural Networks (SBRN 2008). Piscataway, NJ, USA: IEEE; 2008. p. 93–8.
MLA
Antonelo, Eric, Benjamin Schrauwen, and Dirk Stroobandt. “Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing.” 2008 10th Brazilian Symposium on Neural Networks (SBRN 2008). Piscataway, NJ, USA: IEEE, 2008. 93–98. Print.