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Real-time coordinated trajectory planning and obstacle avoidance for mobile robots

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A novel method for real-time coordinated trajectory planning and obstacle avoidance of autonomous mobile robot systems is presented. The desired autonomous system trajectories are generated from a set of first order ODEs. The solution to this system of ODEs converges to either a desired target position or a closed orbit de.ned by a limit cycle. Coordinated control is achieved by utilizing the nature of limit cycles where independent, non-crossing paths are automatically generated from different initial positions that smoothly converge to the desired closed orbits. Real-time obstacle avoidance is achieved by specifying a transitional elliptically shaped closed orbit around the nearest obstacle blocking the path. This orbit determines an alternate trajectory that avoids the obstacle. When the obstacle no longer blocks a direct path to the original target trajectory, a transitional trajectory that returns to the original path is defined. The coordination and obstacle avoidance methods are demonstrated experimentally using differential-drive wheeled mobile robots.
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Bibliografia
  • [1] R. Murray. Recent research in cooperative control of multivehicle systems. Journal of Dynamic Systems, Measurement, and Control, 2007, 129(5), pp. 571-583.
  • [2] V. Kunchev, L. Jain, V. Ivancevic, A Finn. Path planning and obstacle avoidance for autonomous mobile robots: Areview. In: Proc. of the 10 International Conference on Knowledge-Based Intelligent Information and Engineering Systems, volume 4252 of Lecture Notes in Artificial Intelligence, Springer-Verlag, 2006, pp. 537-544.
  • [3] R. Soltan, H. Ashra.uon, K. Muske. Trajectory planning and coordinated control of robotic systems. In: Proc. of the 2009ASMEIDETC/CIE Conference, 2009.
  • [4] R. Soltan, H. Ashrafiuon, K. Muske. Trajectory realtime obstacle avoidance for underactuated unmanned surface vessels. In: Proc. of the 2009 ASME IDETC/CIE Conference, 2009.
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  • [7] R. Grech, S.G. Fabri. Trajectory tracking in the presence of obstacles using the limit cycle navigation method. In: Proc. of the 20 IEEE International Symposium on Intelligent Control and the 13 Mediterranean Conference on Control and Automation, 2005, pp. 101-106.
  • [8] T. Chikamasa. Embedded coder robot NXT instruction manual, 2009. www.mathworks.com/matlabcentral/fileexchange/ 13399/.
  • [9] L. McNinch, R. Soltan, K. Muske, H. Ashrafiuon, J. Peyton Jones.An experimental mobile robot platform for autonomous systems research and education. In: , in press, 2009.
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bwmeta1.element.baztech-article-BUJ5-0030-0030
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