A Review of Path Planning Method for Mobile Robot

Zong Sheng Wu; Wei Ping Fu

doi:10.4028/www.scientific.net/AMR.1030-1032.1588

Paper Titles

The Research of Embedded System in Industrial Control
p.1570

The Study of BP Neural Network PID Control Based on the Cutting Chatter Suppression System
p.1574

Variable Structure Control of Suspension Rotor System in the Mement Gyro
p.1578

Introduction to Automatic Shutdown System for Flutter Test of High Speed Wind Tunnel
p.1584

A Review of Path Planning Method for Mobile Robot
p.1588

Design and Application of Energy Saving Safety Control Regulator of AC Arc Welding Machine
p.1592

Fuzzy-LQR Based Anti-Swing Control of Gantry Crane
p.1596

Multi-Point Turning System for Flexible Robot Body
p.1602

Simulation Experiment on Travelling Path Control of Differential Wheeled Pipeline Robot
p.1608

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1030-1032A Review of Path Planning Method for Mobile Robot

A Review of Path Planning Method for Mobile Robot

Abstract:

The ability of a mobile robot to plan its path is the key task in the field of robotics, which is to find a shortest, collision free, optimal path in the various scenes. In this paper, different existing path planning methods are presented, and classified as: geometric construction method, artificial intelligent path planning method, grid method, and artificial potential field method. This paper briefly introduces the basic ideas of the four methods and compares them. Some challenging topics are presented based on the reviewed papers.

You might also be interested in these eBooks

Materials, Transportation and Environmental Engineering II

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 1030-1032)

Pages:

1588-1591

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1030-1032.1588

Citation:

Cite this paper

Online since:

September 2014

Authors:

Zong Sheng Wu*, Wei Ping Fu

Keywords:

Artificial Potential Field, Genetic Algorithm (GA), Grid, Path Planning, Voronoi

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] R.A. Brooks: Solving the Find-Path Problem by good representation of free space. IEEE Trans on Sys Man and Cybern, 1983, 13(3): 190-197.

DOI: 10.1109/tsmc.1983.6313112

Google Scholar

[2] B Siciliano, L Sciavicco: A Solution Algorithm to the Inverse Kinematic Problem for Redundant Manipulators[J]. IEEE Journal of Robotics and Automation, 1998(4): 403-410.

DOI: 10.1109/56.804

Google Scholar

[3] P.Y. Zhang, T.S. Lu and L.B. Song: Soccer robot path planning based on the artificial potential field approach with simulated annealing. Robotica, 2004, 22: 563-566.

DOI: 10.1017/s0263574703005666

Google Scholar

[4] P. Vadakkepat, K.C. Tan and W. Ming-Liang: Evolutionary artificial potential fields and their application in real time robot path planning. Proceedings of the 2000 Congress on Evolutionary Computation, Piscataway, New Jersey, 2000, pp.256-263.

DOI: 10.1109/cec.2000.870304

Google Scholar

[5] C. M. Lim, T. Hiyama: Application of fuzzy logic control to a manipulator. IEEE trans. Robotics and Automation, 1991, 7(5): 688-691.

DOI: 10.1109/70.97890

Google Scholar

[6] T. Fraichard, P. Carnier: Fuzzy control to drive car-like vehicles. Robotics and Autonomous Systems, 2001, 24(3): 1-22.

DOI: 10.1016/s0921-8890(00)00096-8

Google Scholar

[7] Yanrong Hu: A Knowledge Based Generic Algorithm for Path Planning of a Mobile Robots. Robotic and Automation. 2004: 4350-4355.

Google Scholar

[8] K.S.N. Ripon, S. Kwong and K.F. Man: A real-coding jumping gene genetic algorithm (RJGGA) for multiobjective optimization. Int. J. Inf. Sci., 2007, 177(2): 632-654.

DOI: 10.1016/j.ins.2006.07.019

Google Scholar