Actions Selection during a Mobile Robot Navigation for the Autonomous Recharging Problem



Título del documento: Actions Selection during a Mobile Robot Navigation for the Autonomous Recharging Problem
Revista: Computación y sistemas
Base de datos:
Número de sistema: 000560627
ISSN: 1405-5546
Autores: 1
1
1
1
Instituciones: 1Instituto Politécnico Nacional, Centro de Investigación en Computación, Ciudad de México. México
Año:
Periodo: Oct-Dic
Volumen: 25
Número: 4
Paginación: 683-693
País: México
Idioma: Inglés
Tipo de documento: Artículo
Resumen en inglés The use of mobile robots has increased for its application in various areas such as supply chains, factories, cleaning, disinfection, medical assistance, search, and exploration. It is a fact that most of these robots, if not all, use batteries to power themselves. During a mobile robot task execution, the battery's electric charge tends to deplete as a function of the energy load demands, which would cause the robot to shut down if the discharge is critical, leaving its task inconclusive. Therefore, it is of utmost importance that the robot learns when to charge its batteries, avoiding turning off. This work shows a reactive navigation scheme for a mobile robot that integrates a module for battery-level monitoring. A robot moves from a starting point to a destination according to the battery level. During the navigation, the robot decides when to change the course toward a battery charging station. This paper presents a rules-based reinforcement learning architecture with three entries; these entries correspond to the robot's battery level, the distance to the destination, and the distance to the battery charging station. According to the simulations, the robot learns to select an appropriate action to accomplish its task.
Disciplinas: Ciencias de la computación
Palabras clave: Inteligencia artificial
Keyword: Mobile robot,
Navigation,
Path-planning,
Fuzzy Q-learning,
Artificial potential fields,
Reinforcement learning,
Autonomous recharging problem,
Artificial intelligence
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