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Motion prediction of moving objects in a robot navigational environment using fuzzy-based decision tree approach

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EN
Abstrakty
EN
In a dynamic robot navigation system the robot has to avoid both static and dynamic objects on its way to destination. Predicting the next instance position of a moving object in a navigational environment is a critical issue as it involves uncertainty. This paper proposes a fuzzy rulebased motion prediction algorithm for predicting the next instance position of moving human motion patterns. Fuzzy rule base has been optimized by directional space approach and decision tree approach. The prediction algorithm is tested for real-life bench- marked human motion data sets and compared with existing motion prediction techniques. Results of the study indicate that the performance of the predictor is comparable to the existing prediction methods.
Twórcy
  • Department of Computer Science and Engineering, Gogte Institute of Technology, Belgaum, 590008, India, vijaysr2k@yahoo.com
Bibliografia
  • [1] Foka Amalia, Trahanias Panos E., “Predictive Autonomous Robot navigation”. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, EFPL, Lausanne, Switzerland, Oct. 2002, pp. 490-494.
  • [2] Foka Amalia, Trahanias Panos E., “Predictive control of Robot velocity to avoid objects in dynamic environments” In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 27 -31 October, 2003, Las Vegas, Nevada, pp. 370-375.
  • [3] Gardner Andrew, Pighin Fred, 2001, Motion Capture Web, Retrieved July 2008, from University of Southern California websitehttp://projects.ict.usc.edu/graphics/animWeb/humanoid/.
  • [4] Chang Charles C., Song Kai-Taj, “Dynamic motion planning based on Real-Time object Prediction” In: Proceedings of the 1996 IEEE Intl. Conference on Robotics and Automation, Minnesota, USA.
  • [5] Laugier C., Petti S., “Navigation in Open and Dynamic Environments” In: IEEE International Conference on Robotics and Automation (ICRA'05), 2005, Barcelona, Spain.
  • [6] Huang Hong, Chang Liuchen, “Simulation study on the membership functions of the basic logic controller for the electric vehicle propulsion systems”. In: Canadian Conference on Electrical and Computer Engineering, Calgary, Canada, May 1996, pp. 1004-1007.
  • [7] Yu Huiming, Su Tong, “A Destination Driven Navigator with Dynamic Object Motion Prediction”. In: International Conference on Robotics 2L Automation, Seoul, Korea. 21 -26 May, 2001, pp. 2692-2697.
  • [8] Zhao Jin, Bose Bimal K., “Evaluation of membership functions for fuzzy logic controlled induction motor drive”. IECON Proceedings (Industrial Electronics Conference), volume 1, 2002, pp. 229-234.
  • [9] Kalman R., “A New Approach to Linear Filtering and Prediction Problem”, Transactions of the ASME-Journal of Basic Engineering, vol. 82, 1960, pp. 35-45.
  • [10] Webb P., Fayad C., Brettenbatch C., “The integration of an optimized Fuzzy logic navigation algorithm into a semi-autonomous Robot Control System” In: International Workshop on Recent Advances in Mobile Robots, Leicester, UK, 29 June 2000.
  • [11] Motion Capture Database, Retrieved July 2008 from Carnegie Mellon University Motion Capture Database website: http://mocap.cs.cmu.edu/, funding from NSFEIA-0196217.
  • [12] Madhavan R., Schlenoff C., Moving Object Prediction for Off-road Autonomous Navigation. SPIE Aerosense conference, Orlando, 21 -25 April, 2003.
  • [13] Fisher Robert, Santos-Victor Jose, James Crowley (2001), CAVIAR Video Sequence Ground Truth, Retrieved Jan 2008,fromhttp://homepages.inf.ed.ac.uk/rbf/ CAVIAR/, funded by EC Funded CAVIAR project/IST 2001 37540.
  • [14] Berkan Riza C., Trubatch Sheldon L., Fuzzy Systems Design Principles: Building Fuzzy If-Then Rule Bases. John Wiley & Sons Inc., 1997.
  • [15] Irajit R., Manzuri-Shalmanit M. T., “A New Fuzzy-Based Spatial Model for Robot Navigation among Dynamic Obstacles”. In:IEEE International Conference on Control and Automation, Guangzhou, China, 30 May - 1 une, 2007, pp. 1323-1328.
  • [16] Rajpurohit Vijay S., Pai Manohara M. M., “Feature Extraction Learning For Stereovision Based Robot 14 IEEE International Conference on Advanced Computing Communications - ADCOM 2006, pp. 362-365, ISBN-1-4244-0715-X, NITK, Surathkal, Mangalore, 20 -23 , December 2006.
  • [17] Nam Yun Seok, Lee Bum Hee, Kim Moon Sang, “View-Time Based Moving Object Avoidance using Stochastic Prediction of Object Motion”. In: IEEE International Conference on Robotics and Automation, Minneapolis, Minnesota, USA, April 1996.
  • [18] Hui-Zhong Zhuang, Du Shu-Xin, Wu Tie-jun, “On-line real-time path planning of mobile Robots in dynamic uncertain environment”. Journal of Zheing University Science A, 2006, pp. 516-524.
  • [19] Zhu Q., “Hidden Markov Model for Dynamic Object Avoidance of Mobile Robot Navigation”, IEEE Transactions on Robotics and Automation, 1991, pp. 390-396.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUJ5-0027-0049
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