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Multi Objective Optimization of Trajectory Planning of Non-holonomic Mobile Robot in Dynamic Environment Using Enhanced GA by Fuzzy Motion Control and A*

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Neural Networks and Artificial Intelligence (ICNNAI 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 440))

Abstract

a new hybrid approach based on Enhanced Genetic Algorithm by modified the search A* algorithm and fuzzy logic system is proposed to enhance the searching ability greatly of robot movement towards optimal solution state in static and dynamic environment. In this work, a global optimal path with avoiding obstacles is generated initially. Then, global optimal trajectory is fed to fuzzy motion controller to be regenerated into time based trajectory. When unknown obstacles come in the trajectory, fuzzy control will decrease the robot speed. The objective function for the proposed approach is for minimizing travelling distance, travelling time, smoothness and security, avoiding the static and dynamic obstacles in the robot workspace. The simulation results show that the proposed approach is able to achieve multi objective optimization in dynamic environment efficiently.

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References

  1. Hui, N.B., Mahendar, V., Pratihar, D.K.: Time Optimal, Collision-Free Navigation of a Car-Like Mobile Robot Using Neuro-Fuzzy Approaches. Fuzzy Sets and Systems 157, 2171–2204 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  2. Jelena, G., Nigel, S.: Neuro-Fuzzy Control of a Mobile Robot. Neuro Computing 28, 127–143 (2009)

    Google Scholar 

  3. Sugihara, K., Smith, J.: Genetic Algorithms for Adaptive Motion Planning of an Autonomous Mobile Robot. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 138–143 (1997)

    Google Scholar 

  4. Lei, L., Wang, H., Wu, Q.: Improved Genetic Algorithms Based Path Planning of Mobile Robot Under Dynamic Unknown Environment. In: IEEE International Conference on Mechatronics and Automation, pp. 1728–1732 (2006)

    Google Scholar 

  5. Li, X., Choi, B.-J.: Design of Obstacle Avoidance System for Mobile Robot Using Fuzzy Logic Systems. International Journal of Smart Home 7(3), 321–328 (2013)

    MathSciNet  Google Scholar 

  6. Li, X., Choi, B.-J.: Obstacle Avoidance of Mobile Robot by Fuzzy Logic System. In: ISA, ASTL, vol. 21, pp. 244–246. SERSC (2013)

    Google Scholar 

  7. Purian, F.K., Sadeghian, E.: Path Planning of Mobile robots Via Fuzzy Logic in Unknown Dynamic Environments with Different Complexities. Journal of Basic and Applied Scientific Research 3(2s), 528–535 (2013)

    Google Scholar 

  8. Arshad, M., Choudhry, M.A.: Trajectory Planning of Mobile robot in Unstructured Environment for Multiple Objects. Mehran University Research Journal of Engineering & Technology 31(1), 39–50 (2012)

    Google Scholar 

  9. Rusu, C.G., Birou, I.T., Szöke, E.: Fuzzy Based Obstacle Avoidance System for Autonomous Mobile Robot. In: IEEE International Conference on Automation Quality and Testing Robotics, vol. (1), pp. 1–6 (2010)

    Google Scholar 

  10. Rusu, C.G., Birou, I.T.: Obstacle Avoidance Fuzzy System for Mobile Robot with IR Sensors. In: 10th International Conference on Development and Application, pp. 25–29 (2010)

    Google Scholar 

  11. Shi, P., Cui, Y.: Dynamic Path Planning for Mobile Robot Based on Genetic Algorithm in Unknown Environment: In. IEEE Conference on, pp. 4325–4329 (2010)

    Google Scholar 

  12. Benbouabdallah, K., Qi-dan, Z.: Genetic Fuzzy Logic Control Technique for a Mobile Robot Tracking a Moving Target. International Journal of Computer Science Issues 10(1), 607–613 (2013)

    Google Scholar 

  13. Senthilkumar, K.S., Bharadwaj, K.K.: Hybrid Genetic-Fuzzy Approach to Autonomous Mobile Robot. In: IEEE International Conference on Technologies for Practical Robot Applications, pp. 29–34 (2009)

    Google Scholar 

  14. Farshchi, S.M.R., NezhadHoseini, S.A., Mohammadi, F.: A Novel Implementation of G-Fuzzy Logic Controller Algorithm on Mobile Robot Motion Planning Problem. Canadian Center of Science and Education, Computer and Information Science 4(2), 102–114 (2011)

    Google Scholar 

  15. Phinni, M.J., Sudheer, A.P., RamaKrishna, M., Jemshid, K.K.: Obstacle Avoidance of a wheeled mobile robot: A Genetic-neurofuzzy approach. In: IISc Centenary – International Confonference on Advances in Mechanical Engineering (2008)

    Google Scholar 

  16. Oleiwi, B.K., Hubert, R., Kazem, B.: Modified Genetic Algorithm based on A* algorithm of Multi objective optimization for Path Planning. In: 6th International Conference on Computer and Automation Engineering, vol. 2(4), pp. 357–362 (2014)

    Google Scholar 

  17. Oleiwi, B.K., Roth, H., Kazem, B.: A Hybrid Approach based on ACO and GA for Multi Objective Mobile Robot Path Planning. Applied Mechanics and Materials 527, 203–212 (2014)

    Article  Google Scholar 

  18. Kim, C.H., Kim, B.K.: Minimum-Energy Motion Planning for Differential-Driven Wheeld Mobile Robots. Motion Planning Source in Tech. (2008)

    Google Scholar 

  19. Breyak, M., Petrovic, I.: Time Optimal Trajectory Planning Along Predefined Path for Mobile Robots with Velocity and Acceleration Constraints. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 942–947 (2011)

    Google Scholar 

  20. Vivekananthan, R., Karunamoorthy, L.: A Time Optimal Path Planning for Trajectory Tracking of Wheeled Mobile Robots. Journal of Automation, Mobile Robotics & Intelligent Systems 5(2), 35–41 (2011)

    Google Scholar 

  21. Xianhua, J., Motai, Y., Zhu, X.: Predictive fuzzy control for a mobile robot with nonholonomic constraints. In: IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, Helsinki University of Technology, Espoo, Finland (2005)

    Google Scholar 

  22. Buniyamin, N., Sariff, N.B.: Comparative Study of Genetic Algorithm and Ant Colony Optimization Algorithm Performances for Robot Path Planning in Global Static Environments of Different Complexities. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 132–137 (2009)

    Google Scholar 

  23. Buniyamin, N., Sariff, N.B.: An Overview of Autonomous Mobile Robot Path Planning Algorithms. In: 4th IEEE Student Conference on Research and Development, pp. 183–188 (2006)

    Google Scholar 

  24. Krishnan, P.S., Paw, J.K.S., Tiong, S.K.: Cognitive Map Approach for Mobility Path Optimization using Multiple Objectives Genetic Algorithm. In: 4th IEEE International Conference on Autonomous Robots and Agents, pp. 267–272 (2009)

    Google Scholar 

  25. Castillo, O., Trujillo, L.: Multiple Objective Optimization Genetic Algorithms for Path Planning in Autonomous Mobile Robots. International Journal of Computers, Systems and Signals 6(1), 48–63 (2005)

    Google Scholar 

  26. Fonseca, C.M., Fleming, P.J.: An Overview of Evolutionary Algorithms in Multi-objective Optimization. Evolutionary Computing 3(1), 1–16 (1995)

    Article  Google Scholar 

  27. Jun, H., Qingbao, Q.: Multi-Objective Mobile Robot Path Planning based on Improved Genetic Algorithm. In: Proc. IEEE International Conference on Intelligent Computation Technology and Automation, vol. 2, pp. 752–756 (2010)

    Google Scholar 

  28. Geetha, S., Chitra, G.M., Jayalakshmi, V.: Multi Objective Mobile Robot Path Planning based on Hybrid Algorithm. In: 3rd IEEE International Conference on Electronics Computer Technology, vol. 6, pp. 251–255 (2011)

    Google Scholar 

  29. Saffiotti, A.: The use of fuzzy logic for autonomous robot navigation. Soft Computing 1(4), 180–197 (1997)

    Article  Google Scholar 

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Oleiwi, B.K., Al-Jarrah, R., Roth, H., Kazem, B.I. (2014). Multi Objective Optimization of Trajectory Planning of Non-holonomic Mobile Robot in Dynamic Environment Using Enhanced GA by Fuzzy Motion Control and A*. In: Golovko, V., Imada, A. (eds) Neural Networks and Artificial Intelligence. ICNNAI 2014. Communications in Computer and Information Science, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-08201-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-08201-1_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08200-4

  • Online ISBN: 978-3-319-08201-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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