CFP last date
20 May 2024
Reseach Article

Obstacle Avoidance with Virtual sensor in Mobile Robot’s Motion using the Advanced Potential Field Controller

by Marwa T. Yousef, Elsayed M. Saad, Shahira M. Habashy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 4
Year of Publication: 2012
Authors: Marwa T. Yousef, Elsayed M. Saad, Shahira M. Habashy
10.5120/8407-2032

Marwa T. Yousef, Elsayed M. Saad, Shahira M. Habashy . Obstacle Avoidance with Virtual sensor in Mobile Robot’s Motion using the Advanced Potential Field Controller. International Journal of Computer Applications. 53, 4 ( September 2012), 9-14. DOI=10.5120/8407-2032

@article{ 10.5120/8407-2032,
author = { Marwa T. Yousef, Elsayed M. Saad, Shahira M. Habashy },
title = { Obstacle Avoidance with Virtual sensor in Mobile Robot’s Motion using the Advanced Potential Field Controller },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 4 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number4/8407-2032/ },
doi = { 10.5120/8407-2032 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:53:14.859013+05:30
%A Marwa T. Yousef
%A Elsayed M. Saad
%A Shahira M. Habashy
%T Obstacle Avoidance with Virtual sensor in Mobile Robot’s Motion using the Advanced Potential Field Controller
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 4
%P 9-14
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper introduces an Advanced Artificial Potential Field (AAPF) controller which is used to control the robot's motion in cluttered environments. The proposed approach gives less computation and increases the reaction speed of the robot at obstacle avoidance situations. The increasing of robot's reaction speed doesn't affect on the smoothness of its path due to the use of Genetic algorithms (GA) which select the optimum factors of the forces applied to the robot. A measure of smoothness is used to guide the genetic algorithm to select forces' factors with minimum smoothness. Of course more smoothness means less distance and more speed to reach the goal. The Advanced controller using GA is simulated with different cases on Windows Vista using Matlab Software. These cases include environments with single obstacle up to three obstacles and multi-knee corridor. Results are compared to previous works.

References
  1. O. Khatib, "Real-Time Obstacle Avoidance for Manipulators and Mobile Robots", Int. J. Robotics Research, Vol. 5, No. 1, Spring 1986, pp. 90-98.
  2. J. Borenstein and Y. Koren, "The Vector Field Histogram-Fast Obstacle Avoidance for Mobile Robots", IEEE Trans. on Robotics Automation, Vol. 7, No. 3, June 1991, pp. 278-288.
  3. J. Borenstein and Y. Koren, "Obstacle Avoidance with Ultrasonic Sensors", IEEE Journal of Robotics, Vol. 4, No. 2, 1988, pp. 213-218.
  4. E. Shi, T. Cai, C. He and J. Guo, "Study of the New Method for Improving Artificial Potential Field in Mobile Robot Obstacle Avoidance", Proc. of IEEE International Conference on Automation and Logistics, 2007, pp 282-286.
  5. J. Gong, Y. Duan, Y. Man, and G. Xiong, "VPH+: An Enhanced Vector Polar Histogram Method for Mobile Robot Obstacle Avoidance", Proc. of International Conference on Mechatronics and Automation, 2007, pp. 2784-2788.
  6. R. G. Simmons, "The Curvature-Velocity Method for Local Obstacle Avoidance", Proc. of IEEE International Conference on Robotics and Automation, April 1996, pp. 3375-3382.
  7. N. Y. Ko, R. G. Simmons, and K. S. Kim, "A Lane Based Obstacle Avoidance Method for Mobile Robot Navigation", Journal of Mechanical Science and Technology, Vol. 17, No. 11, 2003, pp. 1693-1703.
  8. A. Kelly, "An Intelligent Predictive Control Approach to the High Speed Cross Country Autonomous Navigation Problem", Tech Report CMU-CS-TR-95-33, School of Computer Science, Carnegie Mellon University, 1995.
  9. C. Schlegel, "Fast Local Obstacle Avoidance under Kinematic and Dynamic Constrains for a Mobile Robot", Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998, Vol. 1, pp. 594- 599.
  10. Dong Jin Seo, Nak Yong Ko, and Jung Eun Son, "A Method for Combining Odometry and Distance Sensor Information for Effective Obstacle Avoidance of Autonomous Mobile Robots", International Journal of Control, Automation, and Systems, Vol. 8, No. 3, 2010, pp. 597-603.
  11. Marwa Taher, Hosam Eldin Ibrahim, Shahira Mahmoud, Elsayed Mostafa, "Tracking of a Moving Target by Improved Potential Field Controller in Cluttered Environments", IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 3, March 2012, pp. 472 – 480.
  12. Philip Machler, "Robot Positioning by Supervised and Unsupervised Odometry Correction", PhD thesis, Department of Information, École Poly Technique Federal of Lausanne, 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Artificial Potential Field Obstacle Avoidance Virtual Sensor