LTL Robot Motion Control based on Automata Learning of Environmental Dynamics

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Publikace nespadá pod Fakultu sportovních studií, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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CHEN Yushan TŮMOVÁ Jana BELTA Calin

Rok publikování 2012
Druh Článek ve sborníku
Konference 2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Doi http://dx.doi.org/10.1109/ICRA.2012.6225075
Obor Informatika
Klíčová slova formal methods; robotics; linear temporal logic; Markov chain learning; control strategy synthesis; path planning
Popis 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.
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