Partial Center of Area Method Used for Reactive Autonomous Robot Navigation

  • José Ramón Álvarez-Sánchez
  • Félix de la Paz Lépez
  • José Manuel Cuadra Troncoso
  • José Ignacio Rosado Sánchez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5602)


A new method for reactive autonomous robot navigation using the center of area of detected free space around the robot is described. The proposed method uses only part of detected free space in front of the robot to compute a partial center of area. It is then used to guide the robot in a path suitable for smooth and robust wandering in complex environments. A simple modification in the algorithm can make it useful for obstacle avoidance in reaching a stimulus goal. The proposed method is used in some examples of simulated experiments on map navigation and wandering and it is compared with standard wandering using Aria library from MobileRobots. Also some experiments in obstacle avoidance navigation to reach a stimulus goal are shown in different maps.


Obstacle Avoidance Realistic Sensor Sample Standard Deviation Range Sensor Area Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Álvarez-Sánchez, J.R., de la Paz López, F., Mira, J.M.: On Virtual Sensory Coding: An Analytical Model of Endogenous Representation. In: Mira, J., Sánchez-Andrés, J.V. (eds.) IWANN 1999. LNCS, vol. 1607, pp. 526–539. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  2. 2.
    Álvarez-Sánchez, J.R., Mira, J.M., de la Paz López, F., Troncoso, J.M.C.: The centre of area method as a basic mechanism for representation and navigation. Robotics and Autonomous Systems 55(12), 860–869 (2007)CrossRefGoogle Scholar
  3. 3.
    Cuadra Troncoso, J.M.: Manual de usuario de CyberSim. Dept. Inteligencia Artificial-UNED (September 2007),
  4. 4.
    Cuadra Troncoso, J.M.: Simulación realista de sensores de rango: un enfoque probabilístico. Technical Report R-01, Dept. Inteligencia Artificial-UNED (September 2008),
  5. 5.
    de la Paz López, F., Álvarez-Sánchez, J.R.: Topological Maps for Robot’s Navigation: A Conceptual Approach. In: Mira, J., Prieto, A.G. (eds.) IWANN 2001. LNCS, vol. 2085, pp. 459–467. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  6. 6.
    de la Paz López, F., Sánchez, J.R.Á., Mira, J.M.: An Analytical Method for Decomposing the External Environment Representation Task for a Robot with Restricted Sensory Information. In: Zhou, C., Maravall, D., Ruan, D. (eds.) Autonomous Robotic Systems Soft Computing and Hard Computing Methodologies and Applications, pp. 189–215. Springer, Heidelberg (2003)Google Scholar
  7. 7.
    Koren, Y., Borenstein, J.: Potential field methods and their inherent limitations for mobile robot navigation. In: Proceedings IEEE International Conference on Robotics and Automation, April 1991, pp. 1398–1404 (1991)Google Scholar
  8. 8.
    SensComp, Inc. 600 Series Intrument Transducer Specifications (2004),
  9. 9.
    SICK AG. Technical Description LMS200/211/221/291 Laser Measurement Systems (2006),
  10. 10.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • José Ramón Álvarez-Sánchez
    • 1
  • Félix de la Paz Lépez
    • 1
  • José Manuel Cuadra Troncoso
    • 1
  • José Ignacio Rosado Sánchez
    • 1
  1. 1.Dpto. de Inteligencia ArtificialUNEDMadridSpain

Personalised recommendations