Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2008 | Vol. 2, No. 1 | 5-11
Tytuł artykułu

An ACO Path Planner Using a FIS for Path Selection Adjusted with a Simple Tuning Algorithm

Treść / Zawartość
Warianty tytułu
Języki publikacji
This paper presents a path planner application for mobile robots based on Ant Colony Optimization (ACO). The selection of the optimal path relies in the criterion of a Fuzzy Inference System (FIS), which is adjusted using a Simple Tuning Algorithm (STA). The path planner can be executed in Mode I and Mode II. The first mode only works in the virtual environment of the interface, while Mode II embraces the wireless communication with a real robot; once the ACO algorithm finds the best route, the coordinates are sent to a mobile robot via Bluetooth communication; if the robot senses a new obstacle, the computer is notified and does a rerouting routine in order to avoid the obstacle and reach the goal. In other words, the application supports dynamic search spaces.

Opis fizyczny
Bibliogr. 21 poz., rys.
  • [1] Victor Fernando Mimoz Martinez, Planificación de Trayectorias para Robots Móviles, Doctoral thesis presented on 5th July, 1995. Available at :
  • [2] M. Dorigo, M. Birattari, T. Stiitzle, "Ant Colony Optimization", IEEE Computational Intelligence Magazine, November2006, pp. 28-39.
  • [3] A. P. Engelbrecht, Fundamentals of Computational Swarm Intelligence, Wiley, J England, 2005.
  • [4] A.R. Dieguez, R. Sanz, J. L. Fernandez, "A global motion planner that learns from experience for autonomous mobile robots", Robotics and Computer-Integrated Manufacturing, vol. 25, issue 5, 2007, Elsevier, pp. 544-552.
  • [5] Ashraf Elnagar, Leena Lulu, "A visual tool for computer supported learning: The robot motion planning example", Computers & Education, vol. 49, no. 2, 2007, Elsevier, pp. 269-283.
  • [6] Shuzhi Sam Ge, Xue-Cheng Lai, Abdullah Al Mamun, "Sensor-based path planning for nonholonomic mobile robots subject to dynamie constraints", Robotics and Autonomous Systems, vol. 55, issue 7, 2007, Elsevier, pp. 513-526.
  • [7] K. Gopalakrishnan, S. Ramakrishnan, Optimal Path Planning of Mobile Robot with Multiple Targets Using Ant Colony Optimization. Smart Systems Engineering, 2006, New York, pp. 25-30.
  • [8] L. Zhishuo, C. Yueting, "Sweep based Multiple Ant Colonies Algorithm for Capacitated Vehicle Routing Problem", IEEE International Conference on e-Business Engineering (ICEBE'05), 2005, pp. 387-394.
  • [9] H. Chen, Z. Xu, Path Planning Based on a New Genetic Algorithm, International Conference on Neural Networks and Brain, 2005. Volume 2, 13-15 Oct. 2005, pp. 788-792. Digital Object Identifier 10.1109/ ICNNB. 2005.1614743
  • [10] M. Gemeinder, M. Gerke, "An Active Search Algorithm Extending GA Based Path Planning for Mobile Robot Systems". In: Soft Computing and Industry - Recent Applications, Roy R. et al., (Eds.) Berlin Heidelberg New York: Springer Verlag, 2002, pp. 589-596.
  • [11] M. Tarokh, Path planning ofrovers using fuzzy logic and genetic algorithmf World Automation Conf. ISORA-026, Hawaii, 2000, pp. 1-7.
  • [12] S. Cardenas 0. Castillo, L. Aguilar L, J. Garibaldi, "Intelligent planning and control of robots using genetic algorithms and fuzzy logic", International Conference on Artificial Intelligence (IC-AI '05), 2005, pp.412-418.
  • [13] 0. Castillo, L. Trujillo, "Autonomous mobile robot path planning optimization using multiple objective genetic algorithms", International Conference on Artificial Intelligence (IC-AI W), 2004, pp. 71-76.
  • [14] J. Garibaldi, A. Barreras A., 0. Castillo, "Intelligent Control and Planning of Autonomous Mobile Robots using Fuzzy Logic and Genetic Algorithms". In: Hybrid Intelligent Systems (Edited by 0. Castillo et al.), Springer-Verlag, 2007, pp. 255-265.
  • [15] M. Tarokh, "Genetic Path Planning with Fuzzy Logic Adaptation for Rovers Traversing Rough Terrain". In: Hybrid Intelligent Systems (Edited by Castillo et al.), Springer-Verlag, 2007, pp. 215-228.
  • [16] M. Mohamad, W. Dunningan, "Ant Colony Robot Motion Planning", Computer as a Tool, 2005. EUROCON 2005. The International Conference on, vol. 1, IEEE, 2005, pp. 213-216.
  • [17] W. Ye, D. Ma, H. Fan, "Path Planning for Space Robot Based on The Self-adaptive Ant Colony Algorithm". 1st International Symposium on Systems and Control i n Aerospace and Astronautics, 19-21 January, 2006 (ISSCAA), pp. 4.
  • [18] M. Dorigo, T. Stutzle, Ant Colony Optimization, Bradford, Cambridge, Massachusetts, 2004.
  • [19] E. Gómez Ramirez E., "Simple Tuning of Fuzzy Control-lers". In: The International Conference on Fuzzy Systems, Neural Networks and Genetic Algorithms (FNG 2005), Tijuana, Mexico, 2005, pp. 49-64.
  • [20] Parallax Inc. 2006, Basic Stamp Syntax and Reference Manual. Version 2.2. Available at:
  • [21] A7 Engineering, EmbeddedBlue™ 500 User manual. Available at: downloads/eb5OOUserManual.pdf
Typ dokumentu
Identyfikator YADDA
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.