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  • Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the human can still do a better job, therefore it would be advantageous to create a planner based on data gathered from the robot simulation when humans do the planning. The paper presents the method of using the neural network to transfer the previously gained knowledge into the machine learning based planner. In particular the neural network task is to mimic the planner based on finite state machine. The tests proved that neural network can successfully learn to navigate in constrained environment.
  • Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the human can still do a better job, therefore it would be advantageous to create a planner based on data gathered from the robot simulation when humans do the planning. The paper presents the method of using the neural network to transfer the previously gained knowledge into the machine learning based planner. In particular the neural network task is to mimic the planner based on finite state machine. The tests proved that neural network can successfully learn to navigate in constrained environment. (en)
Title
  • MOBILE ROBOT MOTION PLANNER VIA NEURAL NETWORK
  • MOBILE ROBOT MOTION PLANNER VIA NEURAL NETWORK (en)
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  • MOBILE ROBOT MOTION PLANNER VIA NEURAL NETWORK
  • MOBILE ROBOT MOTION PLANNER VIA NEURAL NETWORK (en)
skos:notation
  • RIV/00216305:26210/11:PU102815!RIV13-MSM-26210___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • S, Z(AV0Z20760514)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...titaPredkladatele
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  • 212800
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26210/11:PU102815
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Mobile robot, motion planning, neural networks (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [40FE0DD7E60A]
http://linked.open...v/mistoKonaniAkce
  • Svratka
http://linked.open...i/riv/mistoVydani
  • Prague
http://linked.open...i/riv/nazevZdroje
  • Engineering Mechanics 2011, 17th International conference may 9-12, 2011, Svratka, Czech republic
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Krejsa, Jiří
  • Věchet, Stanislav
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000313492700075
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Ústav termomechaniky AV ČR
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  • 978-80-87012-33-8
http://localhost/t...ganizacniJednotka
  • 26210
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