CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Three Dimensional Path Planning and Obstacle Avoidance: An Overview

by Duaa A. Ramadhan, Abdulmuttalib T. Rashid
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 30
Year of Publication: 2020
Authors: Duaa A. Ramadhan, Abdulmuttalib T. Rashid
10.5120/ijca2020920336

Duaa A. Ramadhan, Abdulmuttalib T. Rashid . Three Dimensional Path Planning and Obstacle Avoidance: An Overview. International Journal of Computer Applications. 176, 30 ( Jun 2020), 23-27. DOI=10.5120/ijca2020920336

@article{ 10.5120/ijca2020920336,
author = { Duaa A. Ramadhan, Abdulmuttalib T. Rashid },
title = { Three Dimensional Path Planning and Obstacle Avoidance: An Overview },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2020 },
volume = { 176 },
number = { 30 },
month = { Jun },
year = { 2020 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number30/31393-2020920336/ },
doi = { 10.5120/ijca2020920336 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:43:53.189868+05:30
%A Duaa A. Ramadhan
%A Abdulmuttalib T. Rashid
%T Three Dimensional Path Planning and Obstacle Avoidance: An Overview
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 30
%P 23-27
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a survey for a three dimensional path planning algorithms which produced significant attention for the last years. It is dependent on the static and dynamic obstacles when the mobile robot draw it is trajectory to the goal. Also this paper discusses the type of the three dimensional vehicles: The Unmanned Aerial Vehicle (UAV) as a flying robot and the Autonomous Underwater Vehicles (AUVs) as a swimming robot. Two types of data structure are discussed in this paper which represents the navigable area of a virtual environment: the Voxel grid and the volumetric navigation mesh. The differences among the surveyed approaches are discussed and the results are summarized.

References
  1. A. T. Rashid, M. Frasca, A, A, Ali, A. Rizzo and L. Foruna,”Multi-robot localization and orientation estimation using robotic cluster matching algorithm”. Robotics and Autonomous Systems, Vol. 63, p.p. 108-121, 2015.
  2. O. A. Hasan, A. T. Rashid, R. S. Ali and J. Kosha,” A Practical Performance Analysis of Low-Cost Sensors for Indoor Localization of Multi-Node Systems “, Internet Technologies and Applications (ITA), Wrexham UK, September 2017.
  3. O. A. Hasan, A. T. Rashid and R. S. Ali,” Centralized approach for multi-node localization and identification “, Iraq J. Electrical and Electronic Engineering, Vol.12 No. 2, pp. 178-187, 20 1 6.
  4. O. A. Hasan, A. T. Rashid and R. S. Ali,” A Hybrid approach for multi-node localization and Identification “, Basra Journal for Engineering Sciences, vol. 16, no. 2, pp. 11- 20, 2016.
  5. A. T. Rashid, W. H. Zayer and M. T. Rashid,” Design and Implementation of Locations Matching Algorithm for Multi-Object Recognition and Localization”, Iraqi Journal of Electrical and Electronic Engineering, Vol. 14, No. 1, p.p. 10-21, 2018.
  6. A. T. Rashid, A. A. Ali, M. Frasca and L. Fortuna, " Path planning with obstacle avoidance based on visibility binary tree algorithm," Robotics and Autonomous Systems, vol. 61, pp. 1440–1449, 2013.
  7. Z. Y. Ibrahim , A. T. Rashid, and A. F. Marhoon, " An algorithm for Path planning with polygon obstacles avoidance based on the virtual circle tangents", Iraq J. Electrical and Electronic Engineering, Vol. 12, No. 2, pp. 221-234 , 2016.
  8. Z. Y. Ibrahim , A. T. Rashid, and A. F. Marhoon, " Prediction-Based Path Planning with Obstacle Avoidance in Dynamic Target Environment ", Basra Journal for Engineering Sciences, Vol. 16, No. 2, pp. 48 – 60, 2017.
  9. M. Montemerlo, S. Thrun, D. Koller, and B. Webfeet, “Fast SLAM: A factored solution to the simultaneous localization and mapping problem,” Proceedings of the National conference on Artificial Intelligence, 2002, pp. 593–598.
  10. E. Marder-Eppstein, E. Berger, T. Foote, B. Gerkey, and K. Konolige, “The office marathon: Robust navigation in an indoor office environment,” in IEEE International Conference on Robotics and Automation (ICRA), 2010, pp. 300–307.
  11. M. Campbell, M. Egerstedt, J. P. How, and R. M. Murray, “Autonomous driving in urban environments: approaches, lessons and challenges,” Philosophical Trans. of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 368, no. 1928, pp. 4649– 4672, 2010.
  12. R.He, S.Prentice, and N. Roy, “Planning in information space for a quadrotor helicopter in a GPS-denied environment,” in IEEE International Conference on Robotics and Automation (ICRA), 2008, pp. 1814–1820.
  13. J. Tisdale, Z. Kim, and J. Hedrick, “Autonomous UAV path planning and estimation,” IEEE Robotics & Automation Magazine, vol. 16, no. 2, pp. 35–42, 2009.
  14. C. Petres, Y. Pailhas, P. Patron, Y. Petillot, J. Evans, and D. Lane, “Path planning for autonomous underwater vehicles,” IEEE Trans. On Robotics, vol. 23, no. 2, pp. 331–341, 2007.
  15. L.Kravaki, P.Svestka, J.C.Latombe, and M. Overmars, “Probabilistic roadmaps for path planning in high-dimensional configuration spaces,” IEEE Trans. on Robotics and Automation, vol. 12, no. 4, pp. 566–580, 1996.
  16. S. M.LaValle and J.J.Kuffner,“Randomized kinodynamic planning,” International Journal of Robotics Research, vol. 20, no. 5, pp. 378– 400, 2001.
  17. S. Karaman and E.Frazzoli,“Incremental sampling-based algorithms for optimal motion planning,” International Journal of Robotics Research, vol. 30, no. 7, pp. 846–894, 2011.
  18. E. Stumm, A. Breitenmoser, F. Pomerleau, C. Pradalier, and R. Siegwart,“Tensor-voting-based navigation for robotic inspection of 3D surfaces using lidar point clouds,” The International Journal of Robotics Research, vol. 31, no. 12, pp. 1465–1488, Nov. 2012.
  19. Waveren , Rothkrantz 2006.
  20. Edward Angel and Dave Shreiner. Interactive computer graphics: A Top-Down Approach with Shader-Based OpenGL. Pearson Education Limited, 2012.
  21. Samuli Laine and Tero Karras. E_cient sparse voxel octrees{analysis, extensions, and implementation. NVIDIA Corporation, 2, 2010.
  22. Wouter G van Toll, Atlas F Cook IV, and Roland Geraerts. Multi-layered navigation meshes, 2011.
  23. Chyba,M.,Haberkorn,T.,Smith,R.N.,Choi,S.K.,2008.Designandimplementation of time efficient trajectories for autonomous underwater vehicles. Ocean Eng. 35 (1),63–76.
  24. BesadaPortasE.,DeLaTorre,L.,DeLaCruz,J.M.,DeAndrés-Toro,B.,2010. Evolutionary trajectory planner for multiple UAV sin realistic scenarios. IEEE Trans. Robot.26(4),619–634.
  25. Roberge,V.,Tarbouchi,M.,Labonte,G.,2013.Comparisonofparallelgenetic algorithm and particle swarm optimization for real-time UAV path planning. IEEE Trans. Ind.Inf.9(1),132–141.
  26. Alvarez,A.,Caiti,A.,Onken,R.,2004.Evolutionary path planning for autonomous under water vehicles in a variable ocean. IEEE J.Ocean.Eng.29(2),418–429.
  27. Zheng,C.,Li,L.,Xu,F.,Sun,F.,Ding,M.,2005. Evolutionary route planner for unmanned air vehicles. IEEE Trans. Robot. 21 (4), 609–620.
  28. Nikolos,I.K.,Valavanis,K.P.,Tsourveloudis,N.C.,Kostaras,A.N.,2003.Evolutionary algorithm based off line/online path planner for UAV navigation. IEEE Trans. Syst. Man Cybern. BCybern.33(6),898–912.
  29. Hollinger, G.A.; Choudhary, S.; Qarabaqi, P.; Murphy, C.; Mitra, U.; Sukhatme, G.S.; Stojanovic, M.; Singh, H.;Hover, F. Underwater Data Collection Using Robotic Sensor Networks. IEEE J. Sel. Areas Commun. 2012,30, 899–911.
  30. Liu, L.; Liu, Y. On Exploring Data Forwarding Problem in Opportunistic Underwater Sensor Network Using Mobility-Irregular Vehicles. IEEE Trans. Veh. Technol. 2015, 64, 4712–4727.
  31. Smith, R.N.; Huynh, V.T. Controlling Buoyancy-Driven Profiling Floats for Applications in Ocean Observation. IEEE J. Ocean. Eng. 2014, 39, 571–586.
  32. Garau, B.; Alvarez, A.; Oliver, G. Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: An A* Approach. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Shatin, China, 18–22 April 2005; pp. 194–198.
  33. Sun, B.; Zhu, D. Three dimensional D*Lite path planning for Autonomous Underwater Vehicle under partly unknown environment. In Proceedings of the 2016 12thWorld Congress on Intelligent Control and Automation (WCICA), Guilin, China, 12–15 June 2016; pp. 3248–3252.
Index Terms

Computer Science
Information Sciences

Keywords

Three dimensional path planning Multi robot Obstacle avoidance.

Powered by PhDFocusTM