Have a personal or library account? Click to login
An Artificial Potential Field Based Mobile Robot Navigation Method To Prevent From Deadlock Cover

An Artificial Potential Field Based Mobile Robot Navigation Method To Prevent From Deadlock

Journal of Artificial Intelligence and Soft Computing Research
Volume 5 (2015): Issue 3 (July 2015)
By: Tharindu Weerakoon,  Kazuo Ishii and  Amir Ali Forough Nassiraei  
Open Access
|Sep 2015

References

  1. [1] Hwang, Y. K.; Ahuja, N., “Gross motion planning: a survey,” ACM Computing Surveys (CSUR) vol. 24, no.3, 1992, pp.219-291.10.1145/136035.136037
    Search in Google Scholar
  2. [2] Sridharan, K.; Priya T. K., “A parallel algorithm for constructing reduced visibility graph and its FPGA implementation.” Journal of Systems Architecture, vol. 50, no.10, 2004, pp.635-644.10.1016/j.sysarc.2004.02.003
    Search in Google Scholar
  3. [3] Bhattacharya, P.; Gavrilova, M. L., “Roadmap-based path planning-Using the Voronoi diagram for a clearance-based shortest path,” Robotics & Automation Magazine, IEEE, vol.15, no.2, 2008, pp.58-66.10.1109/MRA.2008.921540
    Search in Google Scholar
  4. [4] Garrido, S.; Moreno, L.; Abderrahim, M.; Martin, F., “Path planning for mobile robot navigation using Voronoi diagram and fast marching,” Int. J. Robot. Autom. vol. 2, no.1, 2011, pp.42-64.
    Search in Google Scholar
  5. [5] O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” in Proceedings of IEEE International conference on Robotics and Automation, vol. 2, Stanford, CA, March 1985, pp.500-505.
    Search in Google Scholar
  6. [6] Lai, L. C.; Wu, C. J.; Shiue, Y. L., “A potential field method for robot motion planning in unknown environments,” Journal of the Chinese institute of engineers, vol.30, no.3, 2007, pp.369-377.10.1080/02533839.2007.9671265
    Search in Google Scholar
  7. [7] J., Koren; Y. Borenstein, “Real-Time obstacle avoidance for fast mobile robot,” IEEE Transaction on Systems, Man, and Cybernetics, vol. 19, no. 5, Sep/Oct 1989, pp.1179-1187.10.1109/21.44033
    Search in Google Scholar
  8. [8] Y., Borenstein; J. Koren, “Potential field methods and their inherent limitations for mobile robot navigation,” in Proceedings of the IEEE International Conference on Robotics and Automation, vol.2, 1991, pp.1398-1404.
    Search in Google Scholar
  9. [9] S. S. Ge; Y. J. Cui, “New Potential Functions for Mobile Robot Path Planning,” IEEE Transaction on Robotics and Automation, vol. 16, no. 5, Oct. 2000, pp.615-620.10.1109/70.880813
    Search in Google Scholar
  10. [10] Borenstein, J.; Koren, Y., “Real-time obstacle avoidance for fast mobile robots,” Systems, Man and Cybernetics, IEEE Transactions on, vol.19, no.5, Sept.-Oct. 1989, pp.1179-1187.10.1109/21.44033
    Search in Google Scholar
  11. [11] Yim, W. J.; Park, J. B. “Analysis of mobile robot navigation using vector field histogram according to the number of sectors, the robot speed and the width of the path,” Control, Automation and Systems (ICCAS), 2014 14th International Conference on, vol., no., 22-25 Oct. 2014, pp.1037-1040.10.1109/ICCAS.2014.6987943
    Search in Google Scholar
  12. [12] Chaomin Luo; Yang, S.X.; Krishnan, M.; Paulik, M., “Autonomous vehicle navigation and mapping with local minima avoidance paradigm in unknown environments,” World Automation Congress (WAC), 2014, pp.823-82810.1109/WAC.2014.6936163
    Search in Google Scholar
  13. [13] Jiea, D.; Xueming, M.; Kaixiang, P., “IVFH*: Real-time dynamic obstacle avoidance for mobile robots,” Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on, vol., no., 7-10 Dec. 2010, pp.844-847.10.1109/ICARCV.2010.5707283
    Search in Google Scholar
  14. [14] Bo You; Jiangyan Qiu; Dongjie Li, “A novel obstacle avoidance method for low-cost household mobile robot,” Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on, vol., no., 1-3 Sept. 2008, pp.111-116.10.1109/ICAL.2008.4636130
    Search in Google Scholar
  15. [15] Yata, T.; Kleeman, L.; Yuta, S. I., “Wall following using angle information measured by a single ultrasonic transducer,” Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on, vol.2, no., 16-20 May 1998, pp.1590-1596.
    Search in Google Scholar
  16. [16] Hanafi, D.; Abueejela, Y. M.; Zakaria, M. F., “Wall Follower Autonomous Robot Development Applying Fuzzy Incremental Controller,” Intelligent Control and Automation, vol. 4, no.1, 2013, pp.18-2510.4236/ica.2013.41003
    Search in Google Scholar
  17. [17] Ding, C. J.; Duan, P.; Zhang, M. L.; Han, Y. H., “Wall Following of Mobile Robot Based on Fuzzy Genetic Algorithm of Linear Interpolating,” Fuzzy Information and Engineering, vol. 2., Springer Berlin Heidelberg, 2009, pp.1579-1589.10.1007/978-3-642-03664-4_167
    Search in Google Scholar
  18. [18] Gavrilut, I.; Tiponut, V.; Gacsadi, A.; Tepelea, L., “Wall-following method for an autonomous mobile robot using two IR sensors,” WSEAS International Conference. Proceedings. Mathematics and Computers in Science and Engineering. Eds. N. E. Mastorakis, et al. No. 12. WSEAS, 2008.
    Search in Google Scholar
  19. [19] R. Glasis; A. Komoda; S.A.M. Gielen, “Neural network dynamics for path planning and obstalce avoidance,” Neural Networks, vol. 8, no. 1, 1995, pp. 125-133.10.1016/0893-6080(94)E0045-M
    Search in Google Scholar
  20. [20] C. C. Chang; K. T. Song, “Environment prediction for a mobile robot in a dynamic environment,” IEEE Transaction on Robotics and Automation, vol. 13, no. 6, 1997, pp.862-872.10.1109/70.650165
    Search in Google Scholar
  21. [21] G. Oriolo, “Real-time map building and navigation for autonomous robots in unknown environment,” IEEE Transaction on Systems, Man, and Cybernetics – Part B: Cybernetics, vol. 28, no. 3, 1998, pp. 316-333.10.1109/3477.67862618255950
    Search in Google Scholar
  22. [22] N. H. C. Yung; C. Ye, “Avoidance of moving obstacles through behavior fusion and motion prediction,” IEEE Int. Conf. on Systems, Man, and Cybernetics, San Diego, CA, USA, 1998, pp. 3424-3429.
    Search in Google Scholar
  23. [23] Mohanty, P. K.; Parhi, D. R., “Controlling the motion of an autonomous mobile robot using various techniques: a review,” Journal of Advance Mechanical Engineering, vol.1, no.1, 2013, pp.24-39.10.7726/jame.2013.1003
    Search in Google Scholar
  24. [24] Lee, Gim Hee; Marcelo H. Ang Jr. “Mobile Robots Navigation, Mapping, and Localization Part I,” 2009, pp.1072-1079.10.4018/978-1-59904-849-9.ch158
    Search in Google Scholar
  25. [25] Hacene, N.; Mendil, B., “Autonomous Navigation and Obstacle Avoidance for a Wheeled Mobile Robots: A Hybrid Approach,” International Journal of Computer Applications vol. 81, no.7, 2013, pp.34-37.10.5120/14027-2285
    Search in Google Scholar
  26. [26] Atyabi, A.; Powers, D. M., “Review of classical and heuristic-based navigation and path planning approaches,” International Journal of Advancements in Computing Technology, vol. 5, no.14, 2013.
    Search in Google Scholar
  27. [27] Buniyamin, N.; Wan N. W. A. J.; Sariff, N.; Mohamad, Z., “A simple local path planning algorithm for autonomous mobile robots,” International journal of systems applications, Engineering & development, vol. 5, no. 2, 2011, pp.151-159.
    Search in Google Scholar
  28. [28] Masehian, E.; Sedighizadeh, D., “Classic and heuristic approaches in robot motion planning-a chronological review,” World Academy of Science, Engineering and Technology, vol. 23, 2007, pp.101-106.
    Search in Google Scholar
  29. [29] Li, G.; Tamura, Y.; Yamashita, A.; Asama, H., “Effective improved artificial potential field-based regression search method for autonomous mobile robot path planning,” International Journal of Mechatronics and Automation, vol. 3, no.3, 2013, pp.141-170.10.1504/IJMA.2013.055612
    Search in Google Scholar
  30. [30] L. Tang; S. Dian; G. Gu; K. Zhou; S. Wang; X. Feng, “A Novel potential field method for obstacle avoidance and path planning of mobile robot,” 3rd IEEE Int. Conf. on Computer Science and Technology (ICCSIT), vol. 9, no. 1, 2010, pp. 633-637.10.1109/ICCSIT.2010.5565069
    Search in Google Scholar
  31. [31] Chen, L., “UUV path planning algorithm based on virtual obstacle,” Mechatronics and Automation (ICMA), 2014 IEEE International Conference on. IEEE, 2014.10.1109/ICMA.2014.6885960
    Search in Google Scholar
  32. [32] Lu, W.; Zhang, G.; Ferrari, S., “An Information Potential Approach to Integrated Sensor Path Planning and Control,” Robotics, IEEE Transactions on, vol.30, no.4, Aug. 2014, pp.919-93410.1109/TRO.2014.2312812
    Search in Google Scholar
  33. [33] Doria, N. S. F.; Freire, E. O.; Basilio, J. C., “An algorithm inspired by the deterministic annealing approach to avoid local minima in artificial potential fields,” Advanced Robotics (ICAR), 2013 16th International Conference on, vol., no., 25-29 Nov. 2013, pp.1-6.10.1109/ICAR.2013.6766480
    Search in Google Scholar
  34. [34] Guanghui Li; Yamashita, A.; Asama, H.; Tamura, Y., “An efficient improved artificial potential field based regression search method for robot path planning,” Mechatronics and Automation (ICMA), 2012 International Conference on, vol., no., 5-8 Aug. 2012, pp.1227-1232.
    Search in Google Scholar
  35. [35] Ya-Chun, C.; Yamamoto, Y., “Online deadlock avoidance scheme of wheeled mobile robot under the presence of boxlike obstacles,” Advanced Intelligent Mechatronics. Proceedings, 2005 IEEE/ASME International Conference on, vol., no., 24-28 July 2005, pp.1535-1540.
    Search in Google Scholar
  36. [36] Li, C.; Cui, G.; Lu, H., “The design of an obstacle avoiding trajectory in unknown environment using potential fields,” Information and Automation (ICIA), 2010 IEEE International Conference on, vol., no., 20-23 June 2010, pp.2050-2054.10.1109/ICINFA.2010.5512513
    Search in Google Scholar
  37. [37] Rezaee, H.; Abdollahi, F., “Adaptive artificial potential field approach for obstacle avoidance of unmanned aircrafts,” Advanced Intelligent Mechatronics (AIM), 2012 IEEE/ASME International Conference on, vol., no., 11-14 July 2012, pp.1-6.10.1109/AIM.2012.6305268
    Search in Google Scholar
  38. [38] Lee, J.; Nam, Y.; Hong, S., “Random force based algorithm for local minima escape of potential field method,” Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on. IEEE, vol., no., 7-10 Dec. 2010, pp.827-832.10.1109/ICARCV.2010.5707422
    Search in Google Scholar
  39. [39] Sugiyama, S.; Yamada, J.; Yoshikawa, T., “Path planning of a mobile robot for avoiding moving obstacles with improved velocity control by using the hydrodynamic potential,” Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, vol., no., 18-22 Oct. 2010, pp.1421-1426.10.1109/IROS.2010.5649323
    Search in Google Scholar
  40. [40] Song, Q.; & Liu, L., “Mobile robot path planning based on dynamic fuzzy artificial potential field method,” International Journal of Hybrid Information Technology vol.5, no.4, 2012, pp.85-94.
    Search in Google Scholar
  41. [41] Vadakkepat, P.; Tan, K. C.; Ming-Liang, W., “Evolutionary artificial potential fields and their application in real time robot path planning,” Evolutionary Computation, 2000. Proceedings of the 2000 Congress on. Vol. 1. IEEE, 2000.
    Search in Google Scholar
  42. [42] Melingui, A.; Chettibi, T.; Merzouki, R.; Mbede, J.B., “Adaptive navigation of an omni-drive autonomous mobile robot in unstructured dynamic environments,” Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on, vol., no., 12-14 Dec. 2013, pp.1924-1929.10.1109/ROBIO.2013.6739750
    Search in Google Scholar
  43. [43] Ji-Wung Choi, “A potential field and bug compound navigation algorithm for nonholonomic wheeled robots,” Innovative Engineering Systems (ICIES), 2012 First International Conference on, vol., no., 7-9 Dec. 2012, pp.166-171.10.1109/ICIES.2012.6530864
    Search in Google Scholar
  44. [44] Mohamed, E.F.; El-Metwally, K.; Hanafy, A.R., “An improved Tangent Bug method integrated with artificial potential field for multi-robot path planning,” Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on, vol., no., 15-18 June 2011, pp.555-559.10.1109/INISTA.2011.5946136
    Search in Google Scholar
DOI: https://doi.org/10.1515/jaiscr-2015-0028
Journal RSS Feed
Language: English
Page range: 189 - 203
Published on: Sep 23, 2015
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2015 Tharindu Weerakoon, Kazuo Ishii, Amir Ali Forough Nassiraei, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Previous articleVolume 5 (2015): Issue 3 (July 2015)Next article