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  • We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with partially unknown, changing behavior. The robot is required to achieve an optimal surveillance mission, in which a certain request needs to be serviced repeatedly, while the expected time in between consecutive services is minimized. We define a fragment of Linear Temporal Logic (LTL) to describe such a mission and formulate the problem as a temporal logic game. Our approach is based on two main ideas. First, we extend results in automata learning to detect patterns of the partially unknown behavior of the elements in the environment. Second, we employ an automata-theoretic method to generate the control policy. We show that the obtained control policy converges to an optimal one when the unknown behavior patterns are fully learned. We implemented the proposed computational framework in MATLAB. Illustrative case studies are included.
  • We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with partially unknown, changing behavior. The robot is required to achieve an optimal surveillance mission, in which a certain request needs to be serviced repeatedly, while the expected time in between consecutive services is minimized. We define a fragment of Linear Temporal Logic (LTL) to describe such a mission and formulate the problem as a temporal logic game. Our approach is based on two main ideas. First, we extend results in automata learning to detect patterns of the partially unknown behavior of the elements in the environment. Second, we employ an automata-theoretic method to generate the control policy. We show that the obtained control policy converges to an optimal one when the unknown behavior patterns are fully learned. We implemented the proposed computational framework in MATLAB. Illustrative case studies are included. (en)
Title
  • LTL Robot Motion Control based on Automata Learning of Environmental Dynamics
  • LTL Robot Motion Control based on Automata Learning of Environmental Dynamics (en)
skos:prefLabel
  • LTL Robot Motion Control based on Automata Learning of Environmental Dynamics
  • LTL Robot Motion Control based on Automata Learning of Environmental Dynamics (en)
skos:notation
  • RIV/00216224:14330/12:00057680!RIV13-GA0-14330___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GD102/09/H042), P(LH11065)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 147548
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/12:00057680
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • formal methods; robotics; linear temporal logic; Markov chain learning; control strategy synthesis; path planning (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [AB165633ED4A]
http://linked.open...v/mistoKonaniAkce
  • St Paul, MN
http://linked.open...i/riv/mistoVydani
  • NEW YORK
http://linked.open...i/riv/nazevZdroje
  • 2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Belta, Calin
  • Tůmová, Jana
  • Chen, Yushan
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000309406705032
http://linked.open.../riv/zahajeniAkce
issn
  • 1050-4729
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ICRA.2012.6225075
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 9781467314053
http://localhost/t...ganizacniJednotka
  • 14330
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