The path planning for mobile robot based on bat algorithm

This article presents a novel method of global optimal path planning based on the Dijkstra algorithm and bat algorithm. This method consists of three steps: the first step is establishing the working space of mobile robot by adopting the MAKLINK graph theory, the second step is utilising the Dijkstra algorithm to obtain the sub–optimal path from the start point to the goal point, and the third step is adopting the bat algorithm to optimise the sub–optimal path so as to get the global optimal path of the robot. The result of the simulation experiment shows the proposed method is effective and can meet the real–time requirements of mobile robot. At the same time, the experiment also proves the optimal path planning of mobile robot based on bat algorithm is superior to particle swarm optimisation algorithm.

[1]  Feng Zhi-bin.  The application of the improved potential grid method in robot path planning , 2009 .

[2]  Ruan Xiaogang.  Research and realization of dynamic neural network navigation algorithm for mobile robot , 2010 .

[3]  Ping Zhang,et al.  A Method For Generating Dynamic Security Warning Region in Robotic Teleoperation Based on Artificial Potential Field , 2012 .

[4]  O Hachour,et al.  PATH PLANNING OF AUTONOMOUS MOBILE ROBOT , 2008 .

[5]  Gaige Wang,et al.  A Bat Algorithm with Mutation for UCAV Path Planning , 2012, TheScientificWorldJournal.

[6]  Gao,et al.  Mobile robot path planning method combined improved artificial potential field with optimization algorithm , 2011 .

[7]  Li Lei,et al.  PRESENT STATE AND FUTURE DEVELOPMENT OF MOBILE ROBOT TECHNOLOGY RESEARCH , 2002 .

[8]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[9]  Ying Guan,et al.  A Path Planning Method to Robot Soccer Based on Dijkstra Algorithm , 2012 .

[10]  Tu Dawei.  Vision sensors integration based grid-method for robot real-time obstacle detection , 2011 .

[11]  J. Altringham.  Bats: Biology and Behaviour , 1996 .

[12]  Ali Fallah,et al.  A new approach for robot Path Planning with Genetic Algorithms , 2012 .

[13]  Zhang Heng.  A NOVEL GENETIC ALGORITHM FOR ROBOT PATH PLANNING IN ENVIRONMENT CONTAINING LARGE NUMBERS OF IRREGULAR OBSTACLES , 2004 .

[14]  Hajime Asama,et al.  Efficient method to generate collision free paths for an autonomous mobile robot based on new free space structuring approach , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[15]  Jeng-Shyang Pan,et al.  Bat Algorithm Inspired Algorithm for Solving Numerical Optimization Problems , 2011 .

[16]  Li Cheng,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010 .