Coverage path planning optimization based on Q-learning algorithm

Piardi, Luis; Lima, José; Pereira, Ana I.; Costa, Paulo Gomes da

http://hdl.handle.net/10198/21315

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Autores

Piardi, Luis

Lima, José

Pereira, Ana I.

Costa, Paulo Gomes da

Resumo(s)

Mobile robot applications are increasing its usability in industries and services (examples: vacuum cleaning, painting and farming robots, among others). Some of the applications require that the robot moves in an environment between two positions while others require that the robot scans all the positions (Coverage Path Planning). Optimizing the traveled distance or the time to scan the path, should be done in order to reduce the costs. This paper addresses an optimization approach of the coverage path planning using Q-Learning algorithm. Comparison with other methods allows to validate the methodology.

URI

http://hdl.handle.net/10198/21315

Citação

Piardi, Luis; Lima, José; Pereira, Ana I.; Costa, Paulo (2019). Coverage path planning optimization based on Q-learning algorithm. In 16th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2018). Rhodes, Greece

Editora

AIP Conference Proceedings

DOI

10.1063/1.5114220

Coleções

ESTiG - Publicações em Proceedings Indexadas à WoS/Scopus

Licença CC

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