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IRMA Autonomous Mobile Robot Research

Coordinator (PI): Tomás Arredondo

Contributors: Tomás Arredondo, Wolfgang Freund, César Muñoz, Nicolás Navarro, Fernando Quirós

Start Date: 1st July 2005

End Date: 1st December 2009

This project study and develop behavior based mobile robots. Initially, the project focused on developing new algorithm and methods for mobile robot applications with reduced sensory capabilities or with low cost sensors and actuators. The principal methods that we use include genetic algorithms, genetic programming and fuzzy logic.

Since 2007, the project study state of art algorithms and architectures to determine capabilities and limitations in real world setups. In order to make this process more efficient we divide the process into two stages. In the first stage, we utilize mobile robot simulators. In the second stage, we adapt and develop new algorithms capable of completing tasks in real world scenarios.

The project was started by Prof. Tomás Arredondo, Nicolás Navarro, César Muñoz on the second half of 2005 after a seminar on artificial intelligence. For more information, please visit the project official web site here.

Trajectories - YAKS Mobile robot simulator Trajectories - Scilab visualization
Example of different trajectories generated by our genetic algorithms and fuzzy motivations approach. Left, trajectories displayed in YAKS. Right, trayectories displayed using scilab.

IRMA-IIcc - Mobile robot simulator Real robot trajectories
Left, IRMA-II, our mobile robot platform. Right, Real-world results recorded by a ceilling camera

Related Publications:

  1. Fuzzy Motivations in a Multiple Agent Behaviour-Based Architecture
    International Journal of Advanced Robotic Systems. vol. 10, no. 313, pp. 1-13, Aug 2013
    Arredondo, Tomás; Freund, Wolfgang; Navarro-Guerrero, Nicolás; Castillo, Patricio
    doi, url, Copyright (©) 2013 Arredondo et al., PDF, bibtex, key: Arredondo2013Fuzzy,
  2. Desarrollo e implementación de algoritmo evolutivo multi-objectivo para generar rutas online en un robot móvil autónomo
    Universidad Técnica Federico Santa María. Valparaíso, Chile, Dec 2009 Language: Spanish
    Navarro-Guerrero, Nicolás
    url, Copyright (©) 2009 Navarro-Guerrero, bibtex, key: Navarro-Guerrero2010Desarrollo,
  3. Cooperative Adaptive Behavior Acquisition in Mobile Robot Swarms Using Neural Networks and Genetic Algorithms
    Electronics, Robotics and Automotive Mechanics Conference (CERMA). pp. 417-421, Morelos, Mexico, Sep 2008
    Muñoz, César; Navarro, Nicolás; Arredondo, Tomás; Freund, Wolfgang
    doi, url, ©2008, IEEE, bibtex, key: Munoz2008Cooperative,
  4. Real-Time Adaptive Fuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot
    Mexican International Conference on Artificial Intelligence (MICAI) - Advances in Artificial Intelligence. vol. 4293 of LNCS, pp. 101-111, Apizaco, Mexico, Nov 2006
    Freund, Wolfgang; Arredondo Vidal, Tomás; Muñoz, César; Navarro, Nicolás; Quirós, Fernando
    doi, url, ©2006, Springer-Verlag Berlin Heidelberg, PDF, bibtex, key: Freund2006Real,
  5. Acquiring Adaptive Behaviors of Mobile Robots Using Genetic Algorithms and Artificial Neural Networks
    Electronics, Robotics and Automotive Mechanics Conference (CERMA). vol. 1, pp. 87-91, Cuernavaca, Mexico, Sep 2006
    Navarro, Nicolás; Muñoz, César; Freund, Wolfgang; Arredondo, Tomás
    doi, url, ©2006, IEEE, PDF, bibtex, key: Navarro2006Acquiring,
  6. Fuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot
    International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE). vol. 4031 of LNCS, pp. 462-471, Annecy, France, Jun 2006
    Arredondo, Tomás; Freund, Wolfgang; Muñoz, César; Navarro, Nicolás; Quirós, Fernando
    doi, url, ©2006, Springer-Verlag Berlin Heidelberg, PDF, bibtex, key: Arredondo2006Fuzzy,
  7. A Neural Approach for Robot Navigation Based on Cognitive Map Learning
    International Joint Conference on Neural Networks (IJCNN). pp. 1146-1153, Brisbane, QLD, Australia,
    Yan, Wenjie; Weber, Cornelius; Wermter, Stefan
    doi, url, ©2012, IEEE, key: Yan2012Neural,