Open Access Open Access  Restricted Access Subscription or Fee Access

A Novel Approach To Local Minima Problem In Robot Path Planning Using Artificial Potential Field

Tawseef Ahmed Teli, M Arif Wani

Abstract


The Autonomous mobile robots have vast applications which include industrial robots, service robots, drone-based robots for supplying customer goods, robots for space exploration and much more. Path planning is one of the important steps of using mobile robots in any application. In autonomous mobile robot navigation, local minima describe a situation in which an object gets stuck with no next possible move attainable. This paper introduces a new concept to deal with the local minima problem in Artificial Potential based robot navigation methods. We propose a virtual plane based method which basically gets the robot out of the local minima successfully and inhibits it from getting into the same area again, thereby guaranteeing the convergence of the method. The proposed technique uses the concept of histograms and temporary objectives to achieve its goal. In particular, the histograms are used to find the wide enough gaps for the robot to pass through and the temporary objectives are used to escape the robot from local minima. The above technique is used, in particular, with the C and H type obstacles. The simulation results verify the effectiveness of this method.

Keywords


Artificial potential, Virtual plane, Navigation, Local minima, Histogram, Temporary objectives, Robot

Full Text:

PDF

References


S. Garrido and L. Moreno, “Path planning for mobile robot navigation using voronoi diagram and fast marching,” Intell. Robot. …, no. 2, pp. 42–64, 2006.

O. Hachour, “The proposed Autonomous Mobile Robot Navigation System,” pp. 53–58.

Y. T. János Botzheim and N. Kubota, “Bacterial memetic algorithm for offline path planning of mobile robots,” Memetic Comput. Springer-Verlag, vol. 4, pp. 73–86, 2012.

Q. Z. CenZeng and X. Wei, “GA-based Global Path Planning for Mobile Robot Employing A* Algorithm,” J. Comput., vol. 7, 2012.

H. S. Das, P. K.Behera, S. K. Pradhan, H. K. Tripathy, and P. K. Jena, A Modified Real Time A* Algorithm and Its Performance Analysis for Improved Path Planning of Mobile Robot. Springer India, 2014.

J. Ni, W. Wu, J. Shen, and X. Fan, “An improved VFF approach for robot path planning in unknown and dynamic environments,” Math. Probl. Eng., vol. 2014, 2014.

E. Masehian and Y. Katebi, “Sensor-based motion planning of wheeled mobile robots in unknown dynamic environments,” J. Intell. Robot. Syst. Theory Appl., vol. 74, pp. 893–914, 2014.

O. Khatib, “Real-Time Obstacle Avoidance for Manipulators and Mobile Robots,” Int. J. Rob. Res., vol. 5, pp. 90–98, 1986.

M. G. Park and M. C. Lee, “A New Technique to Escape Local Minimum in Artificial Potential Field Based Path Planning,” KSME Int. J., vol. 17, pp. 1876–1885, 2003.

M. S. Joe Sfeir and H. Saliah-Hassane, “An improved artificial potential field approach to real-time mobile robot path planning in an unknown environment,” in Robotic and Sensors Environments (ROSE), 2011 IEEE International Symposium on, 2011, pp. 208–-213.

M. A. Santiago Garrido Luis Moreno and F. Martin, “Path planning for mobile robot navigation using voronoi diagram and fast marching,” in 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006, pp. 2376–-2381.

G. Li, A. Yamashita, H. Asama, and Y. Tamura, “An efficient improved artificial potential field based regression search method for robot path planning,” 2012 IEEE Int. Conf. Mechatronics Autom., 2012.

D. T. Mei Wang Zhiyong Su and X. Lu, “A hybrid algorithm based on Artificial Potential Field and BUG for path planning of mobile robot,” in Measurement, Information and Control (ICMIC), 2013 International Conference on, 2013, pp. 1393–-1398.

M. Okutomi and M. Mori, “Decision of robot movement by means of a potential field,” Adv. Robot. Taylor Fr., vol. 1, pp. 131–141, 1986.

Z. L. Long-xiang Yang and H. Tang, “A Novel Approach for Path Planning Based on Reactive Behavior-Artificial Potential Filed,” Appl. Mech. Mater., vol. 529, pp. 646–649, 2014.

N. J. Muhammad Zohaib Syed Mustafa Pasha, A. Salaam, and J. Iqbal, “An improved algorithm for collision avoidance in environments having U and H shaped obstacles,” Stud. Inform. Contr, vol. 23, pp. 97–-106, 2014.

X. W. Wenbai Chen and Y. Lu, “An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot,” Cybern. Inf. Technol., vol. 15, 2015.

W. P. Yingchong Ma Gang Zheng and Z. Qiu, “Local path planning for mobile robots based on intermediate objectives,” Robot. Cambridge Univ. Press, pp. 1–15, 2014.

J. Borenstein and Y. Koren, “The vector field histogram-fast obstacle avoidance for mobile robots,” IEEE Trans. Robot. Autom., vol. 7, pp. 278–-288, 1991.

F. D. Andrej Babinec Anton Vitko and M. Dekan, “Navigation of Robot Using VFH+ Algorithm,” J. Mech. Eng. Autom., vol. 3, pp. 303–-310, 2013.

N. E. Pears, “Modeling of a scanning laser range sensor for robotic applications,” Adv. Robot., vol. 13, pp. 549–562, 1998.

Y.-S. Ha and H.-H. Kim, “Environmental map building for a mobile robot using infrared range-finder sensors,” Adv. Robot., vol. 18, pp. 437–450, 2004.

K. V. A. Tsalatsanis and N. Tsourveloudis, “Mobile Robot Navigation Using Sonar and Range Measurements from Uncalibrated Cameras,” J. Intell. Robot. Syst., vol. 48, pp. 253–284, 2007.

W.D.Recken, “Autonomous sonar navigation in indoor, unknown and ustructured environments,” in Proceedings of IEEE IROS, 1994, pp. 431–-438.

J. J. Karthi Balasubramanian Arunkumar R, V. Jayapal, B. A. Chundatt, and J. D. Freeman, “Object recognition and obstacle avoidance robot,” in 2009 Chinese Control and Decision Conference, 2009, pp. 3002–-3006.

D. M. A.Jennings and J. J. Little, “Cooperative robot localization with vision-based mapping,” in Proceedings of IEEE ICRA, 1999, pp. 2659–-2665.

A. K. A.Ohya and A. Kak, “Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing,” IEEE Trans. Robot. Autom., vol. 14, pp. 969–978, 1998.


Refbacks

  • There are currently no refbacks.