Reference : Imitation Learning of an Intelligent Navigation System for Mobile Robots using Reserv...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/36480
Imitation Learning of an Intelligent Navigation System for Mobile Robots using Reservoir Computing
English
Antonelo, Eric Aislan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Schrauwen, Benjamin [> >]
Stroobandt, Dirk [> >]
2008
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN)
IEEE
93-98
Yes
International
978-0-7695-3361-2
Salvador
2008 10th Brazilian Symposium on Neural Networks
26-10-2008 to 30-10-2008
[en] 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 seeking behaviors are reproduced with an increase in stability and robustness over the original controller. Experiments also show that the system generalizes the behaviors for new environments.
http://hdl.handle.net/10993/36480
10.1109/SBRN.2008.32
https://ieeexplore.ieee.org/document/4665898/

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
2008_eric_sbrn.pdfAuthor postprint1.17 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.