Optimized Angular a Star Algorithm for Global Path Search Based on Neighbor Node Evaluation

Full Text (PDF, 311KB), PP.46-52

Views: 0 Downloads: 0


Ankit Bhadoria 1,* Ritesh Kumar Singh 2

1. Deptt. of Computer Science and Engineering, National Institute of Technology, Hamirpur, India

2. Deptt. of Wireless Communication and Computing, Indian Institute Of Information Technology, Allahabad, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2014.08.05

Received: 11 Aug. 2013 / Revised: 20 Dec. 2013 / Accepted: 26 Mar. 2014 / Published: 8 Jul. 2014

Index Terms

A*, Heuristic Function, Euclidean distance, Robot path planning, Partially Unknown Environment


Any electromechanical device can be termed as Robot, which imitates human actions and in some of the situation can be used as a replacement for human. These days Robots are the integral part of our life and can be applied in several applications and tasks by giving respective commands. The research in robotics domain is to make it as autonomous and as much independent as it can be. The problem that arises is of controlling a mobile robot with the energy constraint. A lot of energy is wasted, if it takes wrong trajectory motion, this motion depends upon the robot knowledge which indeed in not constant. The variation in the environment results in making difficult for the robot to take precise and accurate measurements to reach the destination without much of the energy loss. An autonomous robot is expected to take decision according to the situation. For this precise decisions of robot path planning there are algorithms like A*, Dijkstra, D* etc. In this paper we have done analysis on partially known environment situation. Optimal path is planned by new heuristic approach over the A star algorithm, robot moving at an appropriate angle cuts down the unnecessary cost of path planning. Experimental results show that the proposed algorithm is much effective for more than 8% than the conventional A* algorithm in the same map environment.

Cite This Paper

Ankit Bhadoria, Ritesh Kumar Singh, "Optimized Angular a Star Algorithm for Global Path Search Based on Neighbor Node Evaluation", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.8, pp.46-52, 2014. DOI:10.5815/ijisa.2014.08.05




[3]Mohamed Al Marzouqi, Ray A. Jarvis, “Robotic Covert Path Planning: A Survey”, International Conference on Robotics, Automation and Mechatronics, 2011 IEEE. 

[4]DAI Bo, Xiao XIAO-ming, CAI Zi-xing. “Current Status and Future Development of Mobile Robot Path Planning”, Technology Control Engineering of China, May 2005, 12(3):198-202.

[5]Stents, A., “The Focused D* Algorithm for Real-Time Preplanning”. Proceedings of the International Joint Conference on Artificial Intelligence, August 1995, Page(s):1625-1659.

[6]A. Zelinsky, “A mobile robot exploration algorithm”, IEEE Transactions on Robotics and Automation, 1992, 8(2):707-717.

[7]ZHANG Ying, Wu Cheng-dong., “Robot Motion Planning Based on Genetic Algorithms”, Journal of Shenyang Arch. And Civ. Eng. Univ. October 2002,18 (4):302-305.

[8]Dr. M. Jagadeeswari, “An Efficient Architecture for Robotic Path Planning”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 4, April 2012.

[9]Song-Hang Chia, Ant Colony System, “Based Mobile Robot Path Planning”, Fourth International Conference on Genetic and Evolutionary Computing, IEEE 2010.

[10]Adam A. Razavian, “Cognitive Based Adaptive Path Planning Algorithm for Autonomous Robotic Vehicles”, 2005 IEEE.

[11]Linan Zu, Lingling Chen, “Research on Path Planning Method of Multi Mobile Robot in Dynamic Environment”, 2008 IEEE.

[12]Zhou Weiteng, Han Baoming, “Improved Reversely A star Path Search Algorithm based on the Comparison in Valuation of Shared Neighbor Nodes”, ICICIP-2013 IEEE.

[13]Vanitha Aenugu, Peng-Yung Woo “Mobile Robot Path Planning with Randomly Moving Obstacles and Goal”, IJISA Vol.4, No.2, March 2012, DOI: 10.5815/ijisa.2012.02.01 [14] Fabio M. Marchese, “Multiple Mobile Robots Path-Planning with MCA”, 2006 IEEE.

[14]Koenig, S Likhachev, “Fast Replanning for Navigation in Unknown Terrain”, IEEE Transactions on Robotics and Automation. Volume 21, Issue 3, June 2005 Page(s):354-363.

[15]Weijiang Wang, Bingwen Wang, “Research on Virtual Common Information Platform for Intelligent Transportation System Based on Grid Model”, Advances in Systems Science and Applications, Vol.6, No.2 (2006). pp: 304~311.