Comparison and Analysis of Obstacle Avoiding Path Planning of Mobile Robot by Using Ant Colony Optimization and Teaching Learning Based Optimization Techniques

Author(s):  
A. Q. Ansari ◽  
Ibraheem ◽  
Sapna Katiyar
2017 ◽  
Vol 12 (4) ◽  
pp. 12-25 ◽  
Author(s):  
Ibraheem Kasim Ibraheem ◽  
Fatin Hassan Ajeil

This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of ACO algorithm for the same problem with the same environmental conditions by providing the shortest path for multiple testing environments.


2021 ◽  
Author(s):  
Xiuqing Yang ◽  
Ni Xiong ◽  
Yong Xiang ◽  
Mingqian Du ◽  
Xinzhi Zhou ◽  
...  

2009 ◽  
Vol 9 (3) ◽  
pp. 1102-1110 ◽  
Author(s):  
M.A. Porta Garcia ◽  
Oscar Montiel ◽  
Oscar Castillo ◽  
Roberto Sepúlveda ◽  
Patricia Melin

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