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Navigation of autonomous mobile robot using different activation functions of wavelet neural network

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An autonomous mobile robot is a robot which can move and act autonomously without the help of human assistance. Navigation problem of mobile robot in unknown environment is an interesting research area. This is a problem of deducing a path for the robot from its initial position to a given goal position without collision with the obstacles. Different methods such as fuzzy logic, neural networks etc. are used to find collision free path for mobile robot. This paper examines behavior of path planning of mobile robot using three activation functions of wavelet neural network i.e. Mexican Hat, Gaussian and Morlet wavelet functions by MATLAB. The simulation result shows that WNN has faster learning speed with respect to traditional artificial neural network.
Rocznik
Strony
21--34
Opis fizyczny
Bibliogr. 14 poz., rys., tab., wykr., wzory
Twórcy
  • Department of Electrical Engineering, Padmanava College of Engineering, Rourkela, India
autor
  • Department of Electrical Engineering, National Institute of Technology, Dargapur, India
autor
  • Department of Mechanical Engineering, National Institute of Technology, Rourkela, India
Bibliografia
  • [1] R. Abhiyev, D. Ibrahim and B. Erin: Navigation of mobile robots in the presence of obstacles. Elsevier Advances in Engineering Software, 41(10-11), (2010), 1179-1186.
  • [2] S. M. Raghuraman, D. Tamilselviand and N. Shivakumar: Mobile robot navigation using fuzzy logic controller. IEEE Conf. on Control Automation Communication and Energy Conversion, Madurai, India, (2009), 1-5.
  • [3] S. K. Harisha, K. P. Ramakantha, M. Krishna and S. C. Sharma: Fuzzy logic reasoning to control mobile robot on a pre-defined strip-path. World Academy of Science, Engineering and Technology, 42 (2008), 642-646.
  • [4] M. M. Joshi and M. K. Zaveri: Optimally learnt neural network based autonomous mobile robot navigation system. Int. J. on Control System and Instrumentation, 2 (2011), 28-32.
  • [5] D. Janglova: Neural networks in mobile robot motion. Int. J. of Advanced Robotics Systems, 1 (2004), 15-22.
  • [6] D. Z. Jiangand and W. Z Min: Mobile robot path tracking in unknown environment. IEEE Conf. in Robotics, Automation and Mechatronics, Chengdu, China, (2008), 1201-1205.
  • [7] A. Haddad and M. Khatib: Reactive navigation in outdoor environment using potential fields. Proc. of IEEE Int. Conf. on Robotics & Automation, Leuven, Belgium, 2 (1998), 1232-1237.
  • [8] L. Huang: A potential field approach for controlling a mobile robot to track a moving target. IEEE Int. Symp. on Intelligent Control, Singapore, (2007), 65-79.
  • [9] H. Nobario, S. Wazumi, S. Fukuda and S. Arimoto: A potential approach for a mobile robot on an implicit potential field without generation of local minima. IEEE Int. Conf. on Intelligent Robots and Systems, Taukube, Japan, (1989), 70-77.
  • [10] A. Baker: A novel mobile robot navigation system using neuro-fuzzy rule-based optimization technique. J. of Applied Sciences and Technology, 4 (2012), 2577- 2583.
  • [11] Y. Gigras and K. Gupta: Artificial intelligence in robot path planning. Int. J. of Soft Computing and Engineering, 2(2), (2012), 1203-1209.
  • [12] V. Castro, J. P. Neira, C.L. Rueda and J. C. Villamizar: Autonomous navigation strategies for mobile robots using a probabilistic neural network. IEEE Conf. of Electronics Society, Taipei, Taiwan, (2007), 2795-2800.
  • [13] N. Buniyamin, W. A. J. Wanngah, N. Sariff and Z. Mohamad: A simple local path planning algorithm for autonomous mobile robots. Int. J. of Systems Applications, Engineering and Development, 5(2), (2011), 107-120.
  • [14] P. K. Panigrahi, S. Ghosh and D. R. Parhi: A novel intelligent mobile robot navigation technique for avoiding obstacles using RBF neural Nnetwork. IEEE Int. Conf. on Control, Instrumentation, Energy and Communication, Calcutta, India, (2014), 51-56.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0a7caca7-1268-44ed-9a08-43650e9214eb
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