Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots

Nattanmai Parasuraman, Ramviyas, Pagala, Prithvi Sekha and Ferre Pérez, Manuel ORCID: https://orcid.org/0000-0003-0030-1551 (2014). Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots. En: "ISMS 2014. Fifth International Conference on Intelligent Systems, Modelling and Simulation", 27 – 29 January 2014, Langkawi, Malaysia.

Descripción

Título: Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: ISMS 2014. Fifth International Conference on Intelligent Systems, Modelling and Simulation
Fechas del Evento: 27 – 29 January 2014
Lugar del Evento: Langkawi, Malaysia
Título del Libro: ISMS 2014. Fifth International Conference on Intelligent Systems, Modelling and Simulation
Fecha: 2014
Materias:
ODS:
Palabras Clave Informales: Mobile robots, Energy management, Energy optimization, Energy prediction, Energy consumption models
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

Más información

ID de Registro: 30873
Identificador DC: https://oa.upm.es/30873/
Identificador OAI: oai:oa.upm.es:30873
URL Oficial: http://isms2014.info/
Depositado por: Memoria Investigacion
Depositado el: 31 Oct 2014 18:30
Ultima Modificación: 23 Feb 2017 14:05