Path Planning Approach in Unknown Environment

+ 作者地址

  • 摘要
  • 参考文献
  • 相关文章
  • 统计
This paper presents a new algorithm of path planning for mobile robots, which utilises the characteristics of the obstacle border and fuzzy logical reasoning. The environment topology or working space is described by the time-variable grid method that can be further described by the moving obstacles and the variation of path safety. Based on the algorithm, a new path planning approach for mobile robots in an unknown environment has been developed. The path planning approach can let a mobile robot find a safe path from the current position to the goal based on a sensor system. The two types of machine learning: advancing learning and exploitation learning or trial learning are explored, and both are applied to the learning of mobile robot path planning algorithm. Comparison with A* path planning approach and various simulation results are given to demonstrate the efficiency of the algorithm. This path planning approach can also be applied to computer games.

[1] S.M.LaVall .Planning Algorithms[OL].,2010-1-10.

[2] Q.J.Peng;X.M.Kang;T.T.Zhao .Effective virtual reality based building navigation using dynamic loading and path optimization[J].International Journal of Automation and Computing,6(04):335-3432009.

[3] Adding variation to path planning[J].Computer animation and virtual worlds,2008(3/4):p.283-293.

[4] L.Karamouzas;R.Geraerts;M.Overmaxs.Indicative routes for path planning and crowd simulation[A].Orland,USA,2009:113-120.

[5] D.Jung;H.Kim;J.Kim;K.Urn,H.Cho.Efficient path finding in 3D games by using visibility tests with the A* algorithm[A].Marbella,Spain,2004

[6] Yagi Y.;Nishizawa Y. .Map-based navigation for a mobile robot with omnidirectional image sensor COPIS[J].IEEE Transactions on Robotics and Automation,1995(5):634-648.

[7] J.S.Gutmann;M.Fukuchi;M.Fujita.A floor and obstacle height map for 3D navigation of a humanoid robot[A].Spain:Barcelona,2005:1066-1071.

[8] T.Wang;Q.H.Mehdi;N.E.Gough .An integrated navigation system for AGV based on an environment database[J].International Journal of Computers and Their Application,1999,6(01):14-24.

[9] J.Borestein;Y.Koren .Real time obstacle avoidance for fast mobile robots[J].IEEE Transactions on Systems Man and Cybernetics,1989,19(05):1179-1187.

[10] Borenstein J.;Koren Y. .Obstacle avoidance with ultrasonic sensors[J].IEEE journal of robotics and automation,1988(2):213-218.

[11] G.Bauzil;M.Briot;P.Ribes.A navigation subsystem using ultrasonic sensors for the robot Hilare[A].Stratford-upon-Avon,UK,1981:47-58.

[12] T.Kimura;T.Iokibe;H.Sasaki .Fuzzy path planning system for an autonomous vehicle[J].Japanese Journal of Fuzzy theory and Systems,1993,5(04):626-636.

[13] Cheng-Dong Wu,Ying Zhang,Meng-Xin Li,Yong Yue.A Rough Set GA-based Hybrid Method for Robot Path Planning[J].国际自动化与计算杂志(英),2006(01):29-34.

[14] I.J.Griffiths;Q.H.Mehdi;T.Wang;N.E.Gough.A genetic algorithm for path planning[A].Juan-Les-Pins,France,1997:531-536.

[15] T.R.Wan;H.Chen;R Earnshaw.Real-time path planning for navigation in unknown environment[A].University of Birmingham,UK,2003:138-145.

[16] T.Wang;Q.H.Mehdi;N.E.Gough .A human imitation approach to navigation and control of AGVs[J].Chinese Journal of Advanced Software Research,1999,6(02):137-143.

[17] N.D.Richards;M.Sharma;D.G.Ward.A hybrid A*/automaton approach to on-line path planning with obstacle avoidance[A].Chicago,Illinois,USA,2004:20-22.

[18] T.Lozano-Pdrez;M.A.Wesley .An algorithm for planning collision free paths among polyhedral obstacles[J].Communications of the ACM,1979,22(10):560-570.

[19] L.R(a)de;B.Westergren.Mathematics Handbook for Science and Engineering[M].Springer-verlag,2004

[20] N.Bourbaki.Topological vector spaces[M].Elements of Mathematics,Springer,1987


语种: 英文   

  • + 更多
  • 字体大小